Information management system for product ingredients

ABSTRACT

A method for parsing information from a plurality of product labels using information technology. The method includes obtaining constituent information with an ingredient data platform from text and graphics found on a portion of a label from a plurality of the product labels and assigning base attributes automatically with the ingredient data platform to each piece of the constituent information on at least one of the product labels. The method includes associating the base attributes assigned by the ingredient data platform with different base attributes in at least one pre-constructed taxonomy data structure handled by the ingredient data platform to establish relationships between the base attributes that were previously assigned with the ingredient data platform and the base attributes from the pre-constructed taxonomy data structure. The method includes assigning a master attribute automatically with the ingredient data platform to a relationship between the base attributes assigned by the ingredient data platform and the associated base attributes in the pre-constructed taxonomy data structure. The method also includes generating at least a portion of a label view containing detail based on the master attribute pertaining to at least one consumer product whose product label lacks information detailed in the portion of the label view.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application claims the benefit of the followingapplications: U.S. Provisional Application No. 62/372,958, filed Aug.10, 2016, and entitled “Information Management System for ProductIngredients; and U.S. Provisional Application No. 62/468,408, filed Mar.8, 2017, and entitled “Information Management System for ProductIngredients.” The above-captioned applications are hereby incorporatedby reference as if set forth herein in their entirety.

FIELD

The present disclosure relates to an information management computingsystem and related network computing systems for automatically,capturing, analyzing, and manipulating product information, such as forfood products, including an omnibus ingredient detection system thatautomatically detects and deconstructs information typically displayedon the labels of products.

BACKGROUND

A typical food package contains various information, includinginformation about amounts of various ingredients and other information,such as marketing claims, certification information, and the like.However, ingredient text on the packaging can be long and highlycomplex, and many different words can be used to identify the sameingredient or set of ingredients. Ingredients contained in lists arequite frequently nearly incomprehensible to an average consumer, andingredient lists, marketing claims, and other text can also includeconfusing statements such as and/or statements, compound andparenthetical listings, and even somewhat opaque terms like “containsnatural flavors.” The product packaging includes many other graphics andtext that can be more helpful or more confusing to the consumer.Moreover, the product packaging and labeling can vary greatly betweenmanufacturers and retailers, resulting in differing label formats andingredient information that can make it difficult to compare across theproducts from different manufacturers. Ingredients are also difficult tomanage for manufacturers themselves, who may not understand whatstatements they can make that comply with regulatory requirements,requirements of certification, and advertising regulations. As a resultof the complexity and obscurity of ingredient information, manufacturersand retailers may not fully understand competitive products, so it canbe difficult to understand how products should be positioned relative tothird party products. Regulators may also find it difficult to confirmcompliance. Accordingly, the inventors have recognized a need forimproved systems and technology for managing ingredient information.

BRIEF DESCRIPTION OF THE DRAWINGS

The many aspects of the present disclosure and how they may beimplemented in practice are described below by way of non-limitingexamples and with reference to the accompanying drawings.

FIG. 1 is a diagram of an ingredient detection system having aningredient data management platform including a technology stack inaccordance with various aspects of the present disclosure.

FIG. 2 is a diagram of the ingredient data management platform of theingredient detection system and its intake of a label of a product intothe ingredient data management platform in accordance with the presentdisclosure.

FIGS. 3A, 3B, 3C and 3D are partial diagrams that form together anexemplary ingredient data management platform and computing environmentof the ingredient detection system that receives information from thelabel of the product in accordance with the present disclosure.

FIG. 4 is a diagram of an exemplary image capturing computing system inaccordance with the present disclosure.

FIG. 5 is a diagram of an exemplary technology stack for obtainingconstituent information and providing master attributes and additionalinformation to views, APIs, and search systems in accordance with thepresent disclosure.

SUMMARY

The many aspects of the present disclosure include a method fordeconstructing information from a plurality of labels using informationtechnology. The plurality of labels is for a plurality of consumerproducts available to users. The method includes obtaining, using acomputing device, a plurality of labels from the plurality of consumerproducts. Each label of the plurality of labels identifies the contentof a respective consumer product of the plurality of consumer products.The method includes processing, using the computing device, a label ofthe plurality of labels to identify a first piece of constituentinformation corresponding to a first portion of the label and a secondpiece of constituent information corresponding to a second portion ofthe label that is different than the first portion of the label. Themethod includes assigning, using the computing device, a first baseattribute to the first piece of the constituent information andassigning, using the computing device, a second base attribute to thesecond piece of the constituent information. The first base attribute isdescriptive of the first piece of the constituent information and isdifferent than the second base attribute that is descriptive of thesecond piece of the constituent information. The method includesassociating, using the computing device, a first master attribute withat least one of the first base attribute and generating for display at aclient device, a portion of a label view based on a query about at leastone consumer product of the plurality of consumer products, the portionof the label view containing detail of the master attribute.

In the many aspects of the present disclosure, the first and secondpiece of constituent information are each at least one of text andgraphics from a portion of each label in the plurality of label. Theportion of each of the labels in the plurality of label is at least oneof nutrition facts, ingredient listings, certification listings,recycling information, warning listings, certification statements,universal product codes, manufacturers information, marketing claiminformation, and package size.

In the many aspects of the present disclosure, the processing, using thecomputing device, of the label of the plurality of labels to identifythe first piece of constituent information corresponding to the firstportion of the label includes routing the first portion of each of thelabels automatically to an automatic recognition and comparison processfor confirmation of a match between the first base attribute and thefirst piece of the constituent information on each of the labels.

In the many aspects of the present disclosure, the obtaining, using acomputing device, of the plurality of labels from the plurality ofconsumer products includes capturing each of the labels of the pluralityof labels at a scanning device and transmitting the plurality of labelsto the computing device.

In the many aspects of the present disclosure, one of the consumerproducts for which the portion of the label view is generated by thecomputing device in response to the query is related to at least oneitem that is selected from a group consisting of at least one of foods;beverages; consumer packaged goods; personal items; pet care products;clothing; toys for children; lawn care products; window stickers forvehicles; heating, ventilation, air conditioning products; and beddingproducts.

In the many aspects of the present disclosure, the foods are selectedfrom a group consisting of at least one of canned goods, produce, meats,dairy products, and snacks. The beverages are selected from a groupconsisting of at least one of bottled water, fruit juice, vegetablejuice, protein shakes, nutritional shakes, pre-packaged coffee,pre-packaged tea, soda pop, carbonated juices; wines, liquor, beer,mixers, and energy drinks. The personal items are selected from a groupconsisting of at least one of deodorants, toothpastes, mouthwashes,vitamins, herbal supplements wound dressings, cosmetics, skinmoisturizers, sun blocks, anti-itch creams, and sunburn creams. The petcare products are selected from a group consisting of at least one ofdomestic animal foods, treats, litter box materials, topical dressings,and specialized diet mixes. The clothing is selected from a groupconsisting of at least one of undershirts, undergarments, pants, shoes,coats, information about material from which the clothing is made,coatings on the clothing, and treatments on the clothing. The toys forchildren are selected from a group consisting of at least one ofmobiles, teething instruments, baby bottles, toys that can fit into amouth of a child, and pacifiers. The lawn care products are selectedfrom a group consisting of at least one of fertilizers, pesticides, andmoisture retentive media. The window stickers for vehicles are selectedfrom a group consisting of at least one of automobiles, commercialvehicles, off-road vehicles, motorcycles, all-terrain vehicles,lawn-mowing equipment, and snow removal equipment. The heating,ventilation, and air conditioning products are selected from a groupconsisting of at least one of air conditioning handlers, furnaces,humidifiers, de-humidifiers, swamp-coolers, attic fans, media aircleaners, and electrostatic air cleaners. The bedding products areselected from a group consisting of at least one of mattresses, boxsprings, mattress covers, sheets, comforters, duvets, pillows, pillowcases, dust covers, and blankets.

In the many aspects of the present disclosure, the user is a consumeraccessing the computing device with a mobile device through which theuser is able to identify at least one of the consumer products to obtainthe portion of the label view containing the master attributedescriptive of at least one of the consumer products.

In the many aspects of the present disclosure, the portion of the labelview is configured to provide information related to a smartlabel brandlabel. In the many aspects of the present disclosure, the mobile deviceof one of the users is configured to receive QR code data and to presentthe portion of the label view that pertains to the at least one of theconsumer products that is associated with the QR code data. In the manyaspects of the present disclosure, the mobile device is selected from agroup consisting of at least one of a smartphone, a handheld scanner, akiosk by the consumer, a wearable, and a computer.

In the many aspects of the present disclosure, the label view isconfigured to detail other consumer products with which the masterattribute is also associated. In the many aspects of the presentdisclosure, the portion of the label view that contains detail of themaster attribute is also configured to display serving size information.The serving size information is selected from a group consisting of atleast one of a reference amount customarily consumed, a user-adjustableweight per serving, 100 grams of weight per serving, and a recommendeddaily allowance.

In the many aspects of the present disclosure, the portion of the labelview that contains detail of the master attribute is also configured todisplay at least one food code recognized by the National Health andNutrition Examination Survey. The food code is related to the at leastone of the consumer products on which the portion of the label view isbased.

In the many aspects of the present disclosure, one of the users is abrand owner accessing the computing device with a brand owner interfacethrough which the brand owner is able to identify the at least one ofthe consumer products to obtain the portion of the label view containingthe master attribute descriptive of the at least one of the consumerproducts. The brand owner interface is configured to permit the brandowners to input corrective information to be applied to the portion ofthe label view for the one of the consumer products.

In the many aspects of the present disclosure, the brand owner interfaceis configured to include all of the base attributes associated with eachof the many pieces of the constituent information for one of theconsumer products. The computing device is configured to provide thebrand user interface with at least one of a confirmation of a legitimacyof the at least one claim, a suggestion for at least one additionalclaim, and a suggestion for removal of the at least one claim.

In the many aspects of the present disclosure, a method fordeconstructing information from a plurality of labels into constituentinformation using information technology with the plurality of labelsbeing on products for consumers includes obtaining the plurality of thelabels from the consumer products into an ingredient data managementplatform. The method includes detecting automatically with theingredient data management platform each piece among a plurality ofpieces of constituent information from each label in the plurality oflabels and assigning at least a first base attribute automatically withthe ingredient data management platform to a first piece of theconstituent information and to all other pieces of the constituentinformation that match the first base attribute of the first piece ofthe constituent information. The method includes assigning at least asecond base attribute automatically with the ingredient data managementplatform to a second piece of the constituent information and to allother pieces of the constituent information that match the second baseattribute of the second piece of the constituent information. Each ofthe first base attribute and the first piece of the constituentinformation are different from the second base attribute and the secondpiece of the constituent information. The method includes associating amaster attribute automatically with the ingredient data managementplatform to both the first base attribute and the second base attributeand generating a portion of a label view in response to a query about atleast one of the consumer products. The portion of the label viewcontaining detail of at least the master attribute includes informationthat is otherwise unavailable in the pieces of constituent informationof the one of the consumer products to which the label view refers.

In the many aspects of the present disclosure, the portion of the labelview that contains detail of the master attribute is also configured todisplay serving size information. The serving size information isselected from a group consisting of at least one of a reference amountcustomarily consumed, a user-adjustable weight per serving, 100 grams ofweight per serving, and a recommended daily allowance.

In the many aspects of the present disclosure, the ingredient datamanagement platform is configured to be accessed by one of the consumerswith a mobile device through which one of the consumers is able toidentify one of the consumer products to obtain the portion of the labelview. The mobile device is selected from a group consisting of at leastone of a smartphone, a handheld scanner, a kiosk by the consumer, awearable, and a computer.

In the many aspects of the present disclosure, the mobile device of oneof the consumers is configured to receive QR code data. The label viewpertains to one of the consumer products that is associated with the QRcode. The mobile device is one of a smartphone, a handheld scanner, akiosk by the consumer, a wearable, and a computer.

In the many aspects of the present disclosure, detecting automaticallywith the ingredient data management platform includes capturing each ofthe labels of the plurality of labels at a scanning device andtransmitting the plurality of labels to the ingredient data managementplatform.

In the many aspects of the present disclosure, a method for parsinginformation from a plurality of product labels using informationtechnology includes obtaining constituent information with an ingredientdata platform from text and graphics found on a portion of a label froma plurality of the product labels. The method includes assigning baseattributes automatically with the ingredient data platform to each pieceof the constituent information on at least one of the product labels andassociating the base attributes assigned by the ingredient data platformwith different base attributes in at least one pre-constructed taxonomydata structure handled by the ingredient data platform to establishrelationships between the base attributes that were previously assignedto the ingredient data platform and the base attributes from thepre-constructed taxonomy data structure.

The method includes assigning a master attribute automatically with theingredient data platform to a relationship between the base attributesassigned by the ingredient data platform and the associated baseattributes in the pre-constructed taxonomy data structure. The methodincludes generating at least a portion of a label view containing detailbased on the master attribute pertaining to at least one consumerproduct whose product label lacks information detailed in the portion ofthe label view.

In the many aspects of the present disclosure, the portion of eachproduct label includes items of constituent information that are atleast one of nutrition facts, ingredient listings, certificationlistings, recycling information, warning listings, certificationstatements, universal product codes, manufacturers information,marketing claims and package size.

In the many aspects of the present disclosure, the at least one consumerproduct for which the portion of the label view is generated by theingredient data platform is related to one item selected from a groupconsisting of foods; beverages; consumer packaged goods; personal items;pet care products; clothing; toys for children; lawn care products;window stickers for vehicles; heating, ventilation, air conditioningproducts; and bedding products. In the many aspects of the presentdisclosure, the at least one consumer product is foods selected from agroup consisting of at least one of canned goods, produce, meats, dairyproducts, and snacks. The at least one consumer product is beveragesselected from a group consisting of at least one of bottled water, fruitjuice, vegetable juice, protein shakes, nutritional shakes, pre-packagedcoffee, pre-packaged tea, soda pop, carbonated juices; wines, liquor,beer, mixers, and energy drinks. The at least one consumer product ispersonal items selected from a group consisting of at least one ofdeodorants, toothpastes, mouthwashes, vitamins, herbal supplements wounddressings, cosmetics, skin moisturizers, sun blocks, anti-itch creams,and sunburn creams. The at least one consumer product is pet careproducts selected from a group consisting of at least one of domesticanimal foods, treats, litter box materials, topical dressings, andspecialized diet mixes. The at least one consumer product is clothingselected from a group consisting of at least one of undershirts,undergarments, pants, shoes, coats, information about material fromwhich the clothing is made, coatings on the clothing, and treatments onthe clothing. The at least one consumer product is toys for childrenselected from a group consisting of at least one of mobiles, teethinginstruments, baby bottles, toys that can fit into a mouth of a child,and pacifiers. The at least one consumer product is lawn care productsselected from a group consisting of at least one of fertilizers,pesticides, and moisture-retentive media. The at least one consumerproduct is window stickers for vehicles selected from a group consistingof at least one of automobiles, commercial vehicles, off-road vehicles,motorcycles, all-terrain vehicles, lawn-mowing equipment, and snowremoval equipment. The at least one consumer product is heating,ventilation, and air conditioning products selected from a groupconsisting of at least one of air conditioning handlers, furnaces,humidifiers, de-humidifiers, swamp-coolers, attic fans, media aircleaners, and electrostatic air cleaners. The at least one consumerproduct is bedding products selected from a group consisting of at leastone of mattresses, box springs, mattress covers, sheets, comforters,duvets, pillows, pillow cases, dust covers, and blankets.

In the many aspects of the present disclosure, at least one of the usersis a consumer accessing the ingredient data platform with a mobiledevice through which the user identifies at least one of the consumerproducts to obtain a label view containing the portion of the label viewwith the master attribute descriptive of the one the consumer products.In the many aspects of the present disclosure, the portion of the labelview is configured to provide information to support a smartlabel brandview.

In the many aspects of the present disclosure, the mobile device of oneof the users is configured to receive QR code data to present the labelview that pertains to one of consumer products that is associated withthe QR code. In the many aspects of the present disclosure, the mobiledevice is at least one of a smartphone, a handheld scanner, a kioskaccessible by the consumer, a wearable device, a laptop, a notebook, atablet, a smartwatch, and a computer.

In the many aspects of the present disclosure, the label view thatcontains detail of the master attribute is also configured to display atleast the master attribute associated with at least one of a referenceamount customarily consumed, a predetermined weight per serving, 100grams of weight per serving, and a recommended daily allowance.

In the many aspects of the present disclosure, the method includesdetermining that a piece of the constituent information on one of theproduct labels is incorrect. In the many aspects of the presentdisclosure, a label portion is generated to provide correctedinformation for the product labels when it is determined that the pieceof the constituent information on one of the product labels isincorrect.

In the many aspects of the present disclosure, a system includes aningredient data platform that automatically, under computer control,detects items of constituent information from identified product labelsfor consumer products, that assigns base attributes automatically to allof the items of constituent information on the product labels, and thatestablishes relationships between the assigned base attributes withdifferent base attributes in pre-constructed taxonomies. The system alsoassigns a master attribute automatically to at least one of theestablished relationships, and configures at least one data structurefor display in a portion of a label view containing detail of the masterattribute that pertains to at least one of the consumer products. Thedetail of the master attribute contains information unavailable in theconstituent information associated with the at least one of the consumerproducts.

In the many aspects of the present disclosure, the ingredient dataplatform is configured to be accessed by a user with a mobile devicethrough which the user identifies the at least one of the consumerproducts to obtain the portion of the label view containing the masterattribute descriptive of one the at least one of the consumer products.In the many aspects of the present disclosure, the mobile device isconfigured to receive QR code data and to present the label view thatpertains to the at least one of the consumer products that is associatedwith the QR code. The mobile device is at least one of a smartphone, ahandheld scanner, a kiosk accessible by the consumer, a wearable device,a laptop, a notebook, a tablet, a smartwatch, and a computer.

In the many aspects of the present disclosure, the ingredient dataplatform captures automatically at least one of text and graphics fromthe constituent information that includes at least one of nutritionfacts, ingredient listings, certification listings, recyclinginformation, warning listings, certification statements, universalproduct codes, manufacturers information, and package size.

In the many aspects of the present disclosure, the portion of the labelview is configured to provide information to support a smartlabel brandview. In the many aspects of the present disclosure, the label viewdisplays at least the master attribute associated with at least one of areference amount customarily consumed, a predetermined weight perserving, 100 grams of weight per serving, and a recommended dailyallowance.

In the many aspects of the present disclosure, the ingredient dataplatform determines automatically that an item of the constituentinformation on one of the product labels is incorrect.

In the many aspects of the present disclosure, a label portion isautomatically generated to provide corrected information for the productlabel when it is determined that an item of information is incorrect. Inthe many aspects of the present disclosure, the ingredient data platformdetermines automatically that at least one of a nutrition fact, acertification listing, a marketing claim, and a certification statementshould be added to the product label.

The many aspects of the present disclosure include a method forautomatically deconstructing, analyzing, and confirming information on aplurality of labels using information technology. The plurality oflabels is for a plurality of consumer products. The method includesobtaining, using a computing device, a plurality of labels from theplurality of consumer products. Each label of the plurality of labelsidentifies content of a respective consumer product of the plurality ofconsumer products. The method includes processing, using the computingdevice, a label of the plurality of labels to identify constituentinformation on the label including a first set of claims on the label.The method also includes generating a portion of a label view fordisplay at a client device based on a query about at least therespective consumer product associated with the label includingautomatically displaying a second set of claims having at least oneclaim based on the constituent information that is different than anyclaim in the first set of claims.

In the many aspects of the present disclosure, the second set of claimsincludes at least one of a confirmation of a legitimacy of at least oneclaim from the first set of claims. In the many aspects of the presentdisclosure, the second set of claims includes a suggestion for at leastone additional claim. In the many aspects of the present disclosure, thesecond set of claims includes a suggestion for removal of the at leastone claim from the first set of claims. In the many aspects of thepresent disclosure, the second set of claims deletes at least one claimfrom the first set of claims. In the many aspects of the presentdisclosure, the second set of claims substitutes a new claim for the atleast one deleted claim.

In the many aspects of the present disclosure, the constituentinformation is at least one of text and graphics and includes at leastone of nutrition facts, ingredient listings, certification listings,recycling information, warning listings, certification statements,universal product codes, manufacturers information, marketing claiminformation, and package size.

In the many aspects of the present disclosure, the obtaining, using acomputing device, the plurality of labels from the plurality of consumerproducts includes capturing each of the labels of the plurality oflabels at a scanning device and transmitting the plurality of labels tothe computing device.

In the many aspects of the present disclosure, the respective consumerproducts for which the portion of the label view is generated by thecomputing device in response to the query is related to at least oneitem that is selected from a group consisting of at least one of foods;beverages; consumer packaged goods; personal items; pet care products;clothing; toys for children; lawn care products; window stickers forvehicles; heating, ventilation, air conditioning products; and beddingproducts.

In the many aspects of the present disclosure, the foods are selectedfrom a group consisting of at least one of canned goods, produce, meats,dairy products, and snacks. The beverages are selected from a groupconsisting of at least one of bottled water, fruit juice, vegetablejuice, protein shakes, nutritional shakes, pre-packaged coffee,pre-packaged tea, soda pop, carbonated juices; wines, liquor, beer,mixers, and energy drinks. The personal items are selected from a groupconsisting of at least one of deodorants, toothpastes, mouthwashes,vitamins, herbal supplements wound dressings, cosmetics, skinmoisturizers, sun blocks, anti-itch creams, and sunburn creams. The petcare products are selected from a group consisting of at least one ofdomestic animal foods, treats, litter box materials, topical dressings,and specialized diet mixes. The clothing is selected from a groupconsisting of at least one of undershirts, undergarments, pants, shoes,coats, information about material from which the clothing is made,coatings on the clothing, and treatments on the clothing. The toys forchildren are selected from a group consisting of at least one ofmobiles, teething instruments, baby bottles, toys that can fit into amouth of a child, and pacifiers. The lawn care products are selectedfrom a group consisting of at least one of fertilizers, pesticides, andmoisture retentive media. The window stickers for vehicles are selectedfrom a group consisting of at least one of automobiles, commercialvehicles, off-road vehicles, motorcycles, all-terrain vehicles,lawn-mowing equipment, and snow removal equipment. The heating,ventilation, and air conditioning products are selected from a groupconsisting of at least one of air conditioning handlers, furnaces,humidifiers, de-humidifiers, swamp-coolers, attic fans, media aircleaners, and electrostatic air cleaners. The bedding products areselected from a group consisting of at least one of mattresses, boxsprings, mattress covers, sheets, comforters, duvets, pillows, pillowcases, dust covers, and blankets.

In the many aspects of the present disclosure, the client device is amobile device through which a user is able to identify the at least oneof the consumer products to obtain the portion of the label viewdescriptive of at least one the consumer products.

In the many aspects of the present disclosure, the mobile device isselected from a group consisting of at least one of a smartphone, ahandheld scanner, a kiosk by the consumer, a wearable, and a computer.

In the many aspects of the present disclosure, the portion of the labelview is configured to provide information related to a smartlabel brandlabel.

In the many aspects of the present disclosure, a portion of the labelview is configured to display serving size information. The serving sizeinformation is selected from a group consisting of at least one of areference amount customarily consumed, a user-adjustable weight perserving, 100 grams of weight per serving, and a recommended dailyallowance.

In the many aspects of the present disclosure, the client deviceincludes a brand owner interface through which a brand owner is able togenerate a portion of a label view for display including the at leastone claim in the second set of claims.

In the many aspects of the present disclosure, the client deviceincludes a brand owner interface through which the brand owner is ableto generate a portion of a label view that is configured to permit thebrand owner to input corrective information to be applied to the portionof the label view for at least the respective consumer product.

DETAILED DESCRIPTION

Detailed aspects of the present disclosure are provided herein; however,it is to be understood that the disclosed aspects are merely examplesthat may be embodied in various forms. Therefore, specific structuraland functional details disclosed herein are not to be interpreted aslimiting, but merely as a basis for the claims and as a representativebasis for teaching one skilled in the art to variously employ thepresent disclosure in virtually any appropriately detailed structure.

The terms “a” or “an,” as used herein, are defined as one or more thanone. The term “another,” as used herein, is defined as at least a secondor more. The terms “including” and/or “having,” as used herein, aredefined as comprising (i.e., open transition).

The many aspects of the present disclosure include an ingredientmanagement computing system and/or computing environment thatautomatically captures and manages product information typicallycontained on the labels (referred to in some cases herein as labels orlabel flats) of food products or other consumer products. In the manyaspects, the ingredient management computing system and/or computingenvironment 10, as depicted in FIGS. 1 and 2, can be used toautomatically capture, process, parse, and/or otherwise analyze productinformation and/or images of product information captured or otherwiseobtained from labels of a single product, multiple products (e.g., avery large numbers of products), consumer products, and the like. In themany aspects, the obtained product information is automaticallycaptured, recognized, processed, and parsed by the ingredient managementcomputing system and/or computing environment 10 into data, datasets, ortaxonomic data structures of a highly granular level that reflects abase, or atomic, level of each ingredient of which there are manythousands in the aspects of the present disclosure, such that thecomputing environment, the processes, and the systems described in thepresent application are required in order to automatically process,analyze, deconstruct, and parse (e.g., breakdown and organize) the vastamounts ingredient and product data into the pieces or portions of theconstituent information in an efficient, instant, and real-time manner,as well as various intermediate levels of the ingredients and productinformation (such as where an ingredient represents a combination,mixture, compound, or the like). The obtained ingredient and productinformation can then be processed by the ingredient management computingsystem and/or computing environment 10 to automatically generate variousinterfaces and/or graphical user-interfaces (referred to herein astailored views), which may be provided to users, such as consumers,manufacturers (referred to in some cases herein as brands, brand owners,or product owners), retailers, regulators, marketing professionals,service providers, and others, in real-time or near real-time.

In the many aspects of the present disclosure, the ingredient managementcomputing system and/or computing environment 10 includes an ingredientdata management platform 20, as shown in FIG. 1. The ingredient datamanagement platform 20 includes a technology stack of the ingredientmanagement system 10 with various components, modules, and layers thatcan connect with many different users.

The ingredient data management platform 20 can automatically capture,process, parse, and/or otherwise analyze product ingredients and/orproduct information from images obtained from one or many labels 100 ofone or many products 110 including a single label 102 of a singleproduct 112, and on other single products such as a product 114 and aproduct 116. In one aspect, text 104 and graphics 106 on the labels 102can be digitized and deconstructed by the ingredient managementcomputing system and/or environment 10 so that many base attributes 120can be assigned to all or some of constituent information 122 on thelabels 100. The base attributes 120 can be categorized, sorted, andmapped to one or more taxonomic libraries that can be in apreconstructed taxonomic data structure. One or more master attributes124 can be associated with the base attributes 120; or put another way,multiple base attributes 120 can be non-exclusively organized under themaster attributes 124. In certain aspects, one of the master attributes124 can be associated one of the base attributes 120. In furtheraspects, one of the master attributes 124 can be associated with apredetermined set of base attributes 120. In additional aspects, one ofthe master attributes 124 can be associated with the lack of apredetermined set of base attributes 120 being assigned (or in thiscase, not being able to assign) to the constituent ingredients 122 onthe labels 100.

The ingredient data management platform 20 can generate tailored viewsthat can be selected by one of the users of the system or computingenvironment 10. The tailored views (or portions thereof) can display themaster attributes 124. The tailored views can also display at least oneof the master attributes 124, the constituent information 122, the baseattributes 120. In certain examples, the constituent information 122 caninclude or can be used to recreate the actual text 104 and graphics 106from the labels 100. The tailored views (or portions thereof) can beused by many users to make decisions about the products 110 with muchmore information and much more easily understood information relative towhat is set forth on typical product labels. As such, the tailored viewscan display master attributes 124 that are descriptive of products 110and contain information not found or available from the text 104 and thegraphics 106 of the labels 100.

In one example and as shown in label 102, the ingredient managementcomputing system and/or computing environment 10 can be directed to foodproducts, and the label 102 is attached to a consumable productavailable to the buying public in retail channels, such as on shelves ofa store or in an online retail environment. In further examples, theingredient management computing system and/or environment 10 can bedirected to personal items with similar labels such as for deodorants,toothpaste, mouthwash, vitamins, herbal supplements wound dressings,cosmetics, skin moisturizers, sun blocks, anti-itch creams, sunburncreams, and the like. In other examples, the ingredient managementcomputing system and/or computing environment 10 can be directed to petcare products with similar labels such as for domestic animal food,treats, litter box materials, topical dressings, specialized diet mixes,and the like.

In further examples, the ingredient management computing system and/orcomputing environment 10 can be directed to clothing with similar labelssuch as for undershirts, undergarments, pants, shoes, coats, and thelike, such as to contain, in the various aspects, information aboutmaterials, coatings, treatments, or the like for the same. In otherexamples, the ingredient management computing system and/or computingenvironment 10 can be directed to toys for children with similar labelssuch as for mobiles, teething instruments, baby bottles, toys that canfit into a mouth of a child, pacifiers, and the like. In yet furtherexamples, the ingredient management computing system and/or computingenvironment 10 can be directed to lawn care products with similar labelssuch as for fertilizers, pesticides, moisture-retentive media, and thelike. In other examples, the ingredient management computing systemand/or computing environment 10 can be directed to window stickers forvehicles such as for automobiles, commercial vehicles, off-roadvehicles, motorcycles, all-terrain vehicles, lawn-mowing equipment, snowremoval equipment and the like. In further examples, the ingredientmanagement computing system and/or computing environment 10 can bedirected to heating, ventilation, and air conditioning products withsimilar labels such as for air conditioning handlers, furnaces,humidifiers, de-humidifiers, swamp-coolers, attic fans, media aircleaners, electrostatic air cleaners, and the like. Additional examplesinclude the ingredient management computing system and/or computingenvironment 10 being directed to bedding products with similar labelssuch as for mattresses, box springs, mattress covers, sheets,comforters, duvets, pillows, pillow cases, dust covers, blankets, andthe like.

In the many aspects of the present disclosure, the tailored views caninclude a view such as a label view (or a portion thereof). The labelview can be used for food products or other consumer-directed itemsdiscussed herein and can provide more detailed and enhanced labels forthe buyer. In the many aspects of the present disclosure, informationpresented in the tailored view can be used at least in part to create aview that can be used for product verification processes with themanufacturers of the food products, the brand owners, or the like.Information presented in the tailored view through a brand ormanufacturer interface can be used at least in part to create anothertailored view that can be used to determine compliance with regulatorylabeling requirements on food products or the other items discussedherein. Further tailored views can be used to elicit correctiveinformation from the brand owner or manufacturer. Additional tailoredviews can identify claims that could be added or claims that should beomitted from the labels 100 processed by the ingredient data managementplatform 20.

In many aspects of the present disclosure, the constituent information122 can include what is on the package of a product, i.e., every pieceof information. In some aspects, the constituent information 122 can beraw data of the product and its labels delivered in an appropriate datastream or through a suitable communication system. In one example, aserving size of thirty grams can be identified as constituentinformation associated with a food product. By way of this example, theserving size of thirty grams can be considered the raw data from thelabeling on the product. The constituent information 122 can be takenverbatim from the labeling but the serving size of thirty grams andother raw data can be split up and organized into its parts. By way ofthis example, the serving size of thirty grams can be deconstructed andsplit into two pieces of data: 30 units, and the unit of measure isgrams. It will be appreciated in light of the disclosure that number ofunits can be varied as can the units of measure. In one example, asingle unit could be identified such as one unit and the unit of measurebeing in liquid ounces, i.e., 1 oz.

In many aspects of the present disclosure, the base attributes 120 caninclude information derived from the constituent information 122. Inmany aspects, the base attributes 120 can be the building blocks in theingredient management computing system and/or computing environment 10.In many examples, the base attributes 120 can be derived from therecognition of information in the constituent information 122 by runningrecognition processes discussed herein on the constituent information122. In one example, high fructose corn syrup can be constituentinformation 122 listed on the labels 100 and can be recognized by thesystem and/or computing environment 10 and assigned one of many baseattributes 120 including “artificial sweetener.” In a further example,HFCS can be in the constituent information 122 listed on the labels 100in lieu of the labels saying high fructose corn syrup. HFCS can also berecognized by the system and/or computing environment 10 and can beassigned one of many base attributes 120 including “artificialsweetener.”

In many aspects of the present disclosure, the master attribute 124 canbe a “head attribute” under which many of the base attributes 120 can benon-exclusively organized. By way of the previous examples, HFCS can bepart of constituent information 120 on one label 100 while High FructoseCorn Syrup can be part of constituent information 120 on another label100. The base attribute 120 of artificial sweetener can be derived fromboth the HFCS and the high fructose corn syrup constituent information122. The base attribute 120 of artificial sweetener can be organizedunder the master attribute 124 of sweetener. Depending on the use of themaster attributes 124, the base attribute 120 of artificial sweetenercan be organized under other master attributes 124 such as added sugar,non-sucrose sugars, and the like. In further examples, a masterattribute 124 of reduced salt can have base attributes 120 organizedunder it such as low salt, lower salt, or the like. By way of thisexample, the constituent information 122 can be a hint of salt, lowsodium, or comparable statements detailing a reduction in salt content.In this way, all reduced salt claims can be organized and accessed underthe reduced salt master attribute 124 and/or organized under othermaster attributes 124 that relate to the master attributes where baseattributes 120 regarding reduced salt can be helpful such as hearthealth related master attributes 124.

In many aspects of the present disclosure, the text 104 and the graphics106 on the labels 100 can be parsed, deconstructed, and digitized sothat all of the data on the labels 100 and/or further data associatedwith the product can be used to identify and save the constituentinformation 122. The constituent information 122, derived from eitherthe label 100 itself or from other sources, can be stored in arelational database. Various automatic computing methods can be usedincluding machine learning to recognize the patterns in the constituentinformation 122 stored in the relational database. The base attributes120 can be automatically derived from the constituent information 122 topre-process and facilitate the derivation of information from theconstituent information 122 for the ultimate organization under andaccess through the master attributes 124. Once organized under themaster attributes 124, any user can access, confirm, or compare any ofthe constituent information 122 through the relationship with the masterattributes 124.

In many aspects of the present disclosure, the constituent information122 can present additional combinations and patterns of data on whichadditional master attributes 124 can be created. The creation of theadditional master attributes 124 can be performed automatically by theingredient management system 10. Examples of such additional masterattributes 124 can include “Whole Foods Allowed Ingredients,” “BasilIngredients,” “Trans Fat Ingredients,” “Low Sodium Claims,” or the like.The additional combinations and patterns of data recognized in theconstituent information 122 can be directed into one or more NoSQLdatabases or other suitable data stores. In the many aspects of thepresent disclosure, the ingredient management system 10 canautomatically apply many forms of statistical analysis and/or fuzzylogic to automatically and non-exclusively organize the base attributes120 under one or more master attributes 124 based on the one or morerecognized patterns of in the data from the constituent information 122.Any base attributes 120, which are not recognized and as such are notorganized under one or more master attributes 124 (or organized underrelatively few master attributes 124), can be identified for furtheranalysis that can include automatic and manual forms of analyses. Here,the manual forms of analyses can be learned and later emulated by theingredient management system and/or computing environment 10 whencontextual similar base attributes 120 can require further organizationor changes to the organizational strategies. As such, the manual inputsto assist in the organization of the base attributes 120 under themaster attributes 124 can be deployed later under the automaticprocesses of the ingredient management system and/or computingenvironment 10.

With reference to FIG. 2, the labels 100 can include many areas of text104 and many areas of graphics 106, all of this constituent information122 and anything else on the labels 100 can be automatically processed,parsed, deconstructed, and retained by the ingredient data managementplatform 20. The automatic processing, parsing, deconstruction, andretention, of the constituent information 122 can be completed by theingredient data management platform 20 as disclosed herein. Theingredient data management platform 20 can be configured to providethese services resident with the platform 20 or obtain the serviceshosted in the cloud through connectivity with a cloud network facilityor other communication networks.

In the many aspects, the ingredient data management platform 20 canautomatically capture, process, parse, and/or otherwise analyze theconstituent information 122 on the labels 100 to assign one or more ofthe base attributes 120 to each piece of the constituent information122. To make this process more efficient, the ingredient data managementplatform 20 can automatically parse the constituent information 122 intonutrition facts 160, ingredient listings 162, certification listings164, recycling information 166, warning listings 168, and the like. Theingredient data management platform 20 can also automatically processand identify further areas on the label 102 such as the name of themanufacturer 170 and its contact and social media information 172. Theingredient data management platform 20 can also automatically processand identify further areas on the label 102 such container sizes orweights 174, universal price code (UPC) or other machine information 176such as QR codes, batch, serial, and other manufacturing numbers andinformation 178.

In the many aspects of the present disclosure, the ingredient datamanagement platform 20 can receive all (or some) of the constituentinformation 122 on the labels 100 and can automatically process, parse,and/or otherwise analyze all of the text 104 and the graphics 106 ofeach piece of the constituent information 122 and assign at least one ofthe base attributes 120 to each of the pieces of constituent information122. In many instances, more than one of the base attributes 120 can beassigned to each piece of the constituent information 122 for each pieceof information found on the labels 100. In one example, one of the baseattributes 120 can be assigned when a certain ingredient is detected onthe labels 100. Other base attributes 120 can be assigned to othersimilar ingredients on the labels 100. The base attributes 120 can beused to identify the same ingredients from the constituent information122 on labels 100 that can be differently described label-to-label, oreven within a specific label such as the label 102. One of the labels100 can list an ingredient that is equivalent to an ingredient listingon another label. In this instance, the ingredient data managementplatform 20 can assign base attributes 120 to each ingredient anddetermine a relationship between the base attributes 120 based on thelocation of the base attributes (and the ingredients or portion thereofto which they are assigned) in the taxonomic data structures, or thelike that permit organization of the relationships.

By way of example, a common food coloring often known as Yellow 5 isalso known as Tartrazine; however, Yellow 5 can, in fact, be listed onlabels of food products, or other purchasable items described herein inmany different ways (perhaps hundreds or even over one thousanddifferent ways). The ingredient data management platform 20 can assignone of the base attributes 120 that can indicate the presence of Yellow5 (i.e., a head ingredient) in the food product when in fact the labelcontains information showing any one of the many ways to indicate thepresence of Yellow 5 but not actually the word “Yellow 5.” Thus, themany different ways to say Yellow 5 can be captured as base attributes120 and associated with the “contains Yellow 5” or “same as Yellow 5”master attributes 124. In this example, “contains Yellow 5” can be oneof the master attributes 124 that is applied when any of the thousandways to indicate Yellow 5 is used on the labels 100. In a furtherexample when the consumer is one of the users and receives one of thetailored views from the ingredient data management platform 20, theconsumer can be mindful of an allergy to Yellow 5, but otherwise not berequired to be versed in every one of the thousand ways to indicateYellow 5. Thus, the ingredient data management platform 20 can beconstructed to link the many synonyms or near-synonyms in theconstituent information 122 to base attributes 120, so that labelinformation (i.e., the constituent information 122 on the labels 100)can be reduced or deconstructed to sets of master attributes 124 thatare consistently deployed in the ingredient data management platform 20and therefore it can be shown that the users can rely on the masterattributes 124 to better understand the information on the labels 100.

The many aspects of the present disclosure include the ingredient datamanagement platform 20 having many technology layers 200 that canperform one or more functions and interact with or be part of otherlayers 200. The ingredient data management platform 20 can obtain all oftext 104 and graphic 106 textual information from the labels 100including the ingredient data 162 of the products 110. The ingredientdata management platform 20 can also include a new productidentification layer 210. The new product identification layer 210 caninteract with the products 110 and can accept ingredient information,such as by capturing labels 100 into the ingredient data managementplatform 20. In the many aspects of the present disclosure, the newproduct identification layer 210 can interact with an informationderivation layer 220 and a claim identification layer 230 (whichidentifies, for example, marketing claims made on a label) to digitizethe labels 100 with the ingredient data management platform 20 andcategorize the information from the text 104 and the graphics 106 on thelabels 100.

In many aspects of the present disclosure, the new productidentification layer 210 can, under computer control, automaticallycompare the product 110 to an existing dictionary, predeterminedreferences, or the like. The new product identification layer 210 inassociation with its computing environment can then automaticallydetermine based on metadata associated with the product 110, its brand,its manufacturer, or other associated inputs or contextual informationwhether this is a new or the same product or the new or sameingredients, certifications, warnings, container information or thelike. In some aspects, the new product identification layer 210 canautomatically identify new product labels of products that are relatedto products already learned by (i.e., deconstructed and saved in thelibraries and taxonomic structures of) the platform 20 so that featurescommon to the new label and already learned labels need not be learnedagain in this computing environment. In further aspects, the new productidentification layer 210 can also automatically assist in identifyingnew constituent information 122 on a label that can be described in adifferent way whether it is ingredients (e.g. HFCS is High Fructose CornSyrup), product labels, or changes in container labeling orconfiguration.

In many aspects of the present disclosure, the platform 20 and thecomputing environment can include the information derivation layer 220that can automatically analyze patterns on the label 100 of the product110 to determine its constituent information 122 and assist in theassigning of base attributes 120 in the computing environment. In manyaspects of the present disclosure, the claim identification layer 230can automatically analyze patterns in claims identified in the text 104and/or graphics 106 of the label 100 to determine with the computingenvironment the true intent of the identified claims. In one example, a“hint of salt” can be identified in the constituent information 122 andassigned the base attribute 120 that details low sodium.

In further aspects, the ingredient data management platform 20 can havean analytics layer 250 that can associate with the many layers 200 ofthe ingredient data management platform 20, including a cross-productinteraction analysis layer 260 and a market and product positioninganalysis layer 270. Each of these layers 250, 260, 270 can interact withother layers 200, including a user data models layer 300 and a databaselayer 310. The layers 200 can also include a sort layer 320, a comparelayer 330, and a search layer 340 to manipulate all (or some) of themaster attributes 124, the base attributes 120, and the constituentinformation 122 based on labels 100. In many aspects of the presentdisclosure, the analytics layer 250 can, among other things,automatically identify all of the constituent information 122 andanalyze all of the base attributes 120 and master attributes 124 in thecomputing environment. In some examples, the analysis of the baseattributes 120 and master attributes 124 in the computing environmentcan result in the automatic suggestions of claims that can be made about(or should be removed from) the product 100 such as low sodium when suchclaim can be made or removing low sodium when the circumstances dictateit. In many aspects of the present disclosure, the cross-productinteraction analysis layer 260 can automatically use patterns identifiedby the computing environment in one product, in order to determineautomatically similar patterns in identified and analyzed in otherproducts. In many aspects of the present disclosure, the market andproduct positioning analysis layer 270 can automatically determine thecontext of a product as it relates to other products within assigned inits category by the computing environment based on metadata of product.In some examples, the layer 270 can assist the computing environment inautomatically suggesting related products for the user. In furtherexamples, the layer 270 can automatically assist the computingenvironment in automatically identifying constituent information 122 onlabels 100 and automatically assigning base attributes 120 based onproducts positioned in close proximity on a retail shelf offering oroffered in a related position with other products in a web-basedoffering.

In many aspects of the present disclosure, the database layer 310 can bea database of holding pattern information for the computing environmentthat can be used for matching against constituent information 122 duringits automatic identification by the computing environment or itsassigning of base attributes 120 or master attributes 124. In manyaspects of the present disclosure, the sort layer 320 can provide thecomputing environment with the ability to slice, sort, re-sort, arrange,and drill-down automatically into different base attributes 120,constituent information 122, and master attributes 124 using derivedmetadata, contextual information, product positioning, and the like. Inmany aspects of the present disclosure, the compare layer 330 canprovide the computing environment with the ability to compare the baseattributes 120, constituent information 122, and master attributes 124of the products automatically against each other and then re-arrangedbased on the comparison using derived metadata, contextual information,product positioning, and the like. In many aspects of the presentdisclosure, the search layer 340 can provide the computing environmentwith the ability to allow fuzzy searching to gain true intent of searchautomatically to better compare and view the base attributes 120,constituent information 122, and master attributes 124 of the products110.

In further aspects, the ingredient data management platform 20 caninclude a complex definitions layer 350 for determining and catalogingrelatively complex text strings in labels 100 that can include forexample compound ingredient lists with parenthetical statements. Anattributes layer 360, or a hybrid attributes layer 370, or both, caninteract with the other layers 200 of the ingredient data managementplatform 20 to determine master attributes 124 based on the baseattributes 120 assigned to the constituent information 122 for theproducts 110 that can be displayed in tailored views. Those tailoredviews can be based on user profiles or reports, or both. A foodingredients layer 380, or a claims layer 390, or both, can interact withthe other layers 200 of the ingredient data management platform 20 tofurther determine master attributes 124 for the products 110 that can bedisplayed in tailored views.

In many aspects of the present disclosure, the complex definitions layer350 can include core definitions for use in the computing environment.The core definitions can include information about relationships betweenthe base attributes 120, the constituent information 122, and the masterattributes 124 and specifically when certain base attributes areautomatically assigned non-exclusively under one or more masterattributes 124. The core definitions that include information aboutrelationships between the base attributes 120, the constituentinformation 122, and the master attributes 124 can serve as buildingblocks in the computing environment for the attributes layer 360. Theattributes layer 360 can use the building blocks from the computingenvironment and established by the complex definitions layer 350 toautomatically build a wide variety of master attributes 124 based on theprofiles of the user, the needs of the brand owners or manufacturers, orentities looking to confirm the correctness of the constituentinformation 122. The hybrid attributes layer 370 can identify multiplebase attributes 120 or master attributes 124 in the computingenvironment and automatically create additional master attributes 124with a hybrid of other attributes based on the profiles of the user, theneeds of the brand owners or manufacturers, or entities looking toconfirm the correctness of the constituent information 122.

In some aspects of the present disclosure, the ingredient datamanagement platform 20 can be a cloud-based platform and can beconstructed to deliver the software as a service and to allow access viaapplication programming interfaces (APIs) that are suitable for use byvarious users or constituencies, such as allowing API-based accessbetween the ingredient data management platform 20 and informationtechnology systems used by manufacturers, retailers, marketers, and thelike. In further aspects, the ingredient data management platform 20 canconnect to or can include a personalization and recommendation engine400 and a key messaging engine 410. The ingredient data managementplatform 20 can also include a data and analytics user interface 420with a data and analytics application programming interfaces (APIs) 430.The many users of the ingredient data management platform 20 can connectwith an interface or an API, or both, suitable for the needs of thatuser.

In further aspects of the present disclosure, the ingredient datamanagement platform 20 can include a consumer user interface 450 and aconsumer API 460. The consumer user interface 450 can have apersonalized recommendations layer 470, a personalized product attributedisplay layer 480, and a personalized advertising layer 490. Theconsumer user interface 450 can also have a consumer health andnutrition preference layer 500. The consumer user interface 450 can alsoconnect with a smart food product label landing page layer 510, a smartfood product label QR code layer 520, and a digitized smart food productlabel 530. In many aspects of the present disclosure, the personalizedproduct attribute display layer 480 can automatically create a view ofthe product that can be customized with specific attributes available inthe computing environment based on individual user selection. In manyaspects of the present disclosure, the smart food product label landingpage layer 510 can create an exclusive or custom landing page with“deeper” master attributes 124. The deeper master attributes can bederived automatically from the label 100 based on a smart food productas specified by the SmartSPEC brand tailored view. The deeper masterattributes can be automatically configured by information in theSmartSPEC brand tailored view. The deeper master attributes can also beautomatically configured by information from the user, the brand owner,or the like.

In yet further aspects of the present disclosure, the ingredient datamanagement platform 20 can include a brand user interface 550 and abrand user API 560. In other aspects, the ingredient data managementplatform 20 can include a retailer user interface 570 and a retailer API580. The brand user interface 550 and the brand user API 560, theretailer user interface 570, and the retailer user API 580, the consumeruser interface 450 and consumer user API 460 can connect to apersonalization and recommendation engine layer 600. The brand userinterface 550 and the consumer user interface 450 can connect to a smartfood product label landing page layer 610, a smart food product label QRcode layer 620, and a digitized smart food product label layer 630.

In further examples, the retailer user interface 550 can connect with aretailer shelf offerings layer 650. The shelf offering layers 650 can,among other things, locate items in a store on an aisle at a particularshelf location, such as based on the ingredients that may indicate anappropriate aisle (e.g., a “milk” ingredient as one of the majoringredients and a “cheese” statement in a marketing text element mightsuggest the “dairy” aisle for a product). The retailer user interface550 can also connect with a retailer stock supply notification layer 660and a retailer compliance check layer 670 (which may allow compliancepersonnel or computing resources dedicated to compliance to confirm,using information from the platform 20) that a label and/or the productitself complies with applicable regulations, such as FDA regulations orsimilar regulations of other jurisdictions). Through various applicableAPIs, many different users can connect to the ingredient data managementplatform 20 that can include additional layers that can be integral withthe platform 20 or that are connected to add one or more such servicesas needed.

The labels 100 for many products 110 from a manufacturer can be receivedinto the ingredient data management platform 20. The text 104 and thegraphics 106 can form the nutrition facts 160, ingredient listings 162,certification listings 164, recycling information 166, warning listings168, etc. on the labels 100 that can all be received into the ingredientdata management platform 20. As mentioned in the example above, manybase attributes 120 are determined from the constituent information 122found on the labels 100 and relationships to and with detailedtaxonomies that can allow for an understanding of alternative names foringredients (like Yellow 5). Moreover, the base attributes 120 can beassigned based on how constituent ingredients 122 can roll up into otheringredients that are listed in the ingredients area on the labels 100,e.g., compound ingredients. The base attributes 120 can be assigned toeach piece of the product's constituent information 122 and can be usedto better understand and validate (or suggest removal of) claims aboutfoods or other products including claims based on ingredients, healthclaims, and others.

In the many aspects of the present disclosure, the ingredient datamanagement platform 20 can deconstruct all of the information on thelabels 100 and can assign base attributes 120 to all of the information.Similar to the Yellow 5 example above, the many different names can beused to indicate added sugar. By way of this example, a multitude ofingredients (from the constituent information 122) can be recognized andassigned base attributes 120 that are sugar and ingredients comparableto sugar. One of the master attributes 124 can be “Added Sugar” and canbe associated with the respective consumer products 110 having thelabels 100 containing such constituent ingredients 122. The ingredientdata management platform 20 can then identify many food products anddetermine which ones have “Added Sugar” without requiring the user toknow the hundreds of different ingredients that can be added to a foodproduct that amounts to “Added Sugar.” Just like the Yellow 5 example, auser a can inquire about one of the characteristics of a certain foodproduct or many food products and the ingredient data managementplatform 20 can identify those food products without the user having tobe versed in all of the possible sugar contributors or synonyms forYellow 5.

In the various aspects of the present disclosure, the master attributes124 can be delivered to the many users through the tailored views. Themaster attributes 124 can be based on a combination or relationship ofthe base attributes 120, contextual information of the product, the typeof user requesting the information, user profiles, search histories orrelevant analytic results, and the like. The types of users cangenerally include the brand owners or product manufacturers, the retailuser that sell products on a retail basis (like packaged food), and theconsumer. In other instances, government and regulatory bodies such asFood and Drug Administration (FDA) can be a user or any of the one ormore regulatory agencies associated with the products. Each of thesetypes of users can have purposefully distinct uses of the ingredientdata management platform 20 with specific tailored views.

In accordance with the many aspects of the present disclosure, theingredient data management platform 20 enables many distinct use casesfor manufacturers, retailers, and consumers, among others, including usecases related to marketing research, product development, and compliancewith certification processes and government regulators. The use casescan also include product positioning including shelf organization andmarketing claims, and advertising placement and review includingpersonalized recommendations for consumers.

In accordance with present disclosure, the ingredient data managementplatform 20 can provide users with enhanced information relative to whatis listed in the text 104 and the graphics 106 on the labels 100. Thebase attributes 120 can be determined automatically under computercontrol based on what is in each of the different categories recognizedfrom the text 104 and graphics 106 on the labels 100. In certaininstances, the same information in the text 104 and graphics 106,however, can be categorized into at least two categories. Masterattributes 124 can then be automatically assigned to each of theproducts based on the base attributes 120 or the categories in whichthey are organized, or both. In certain aspects of the presentdisclosure, one of the master attributes 124 can be based on at leasttwo of the base attributes 120 in two of the different categories.

For the various use cases detailed herein, the ingredient datamanagement platform 20 can receive many requests from the users that canrequest many different tailored views and include reports listing manymaster attributes 124. The reports when applicable can also include orbe descriptive of base attributes 120 and constituent information 122.In the various aspects of the present disclosure, a subset of masterattributes 124 can be selected automatically when the request from oneof the users is acknowledged or received. The subset of the masterattributes 124 can be based on a combination of the request receivedfrom the user and contextual information (such as a history or likes anddislikes of certain products, variants, or brands) associated with theproduct so that what is delivered can be shown to have an unprecedentedlevel of information helpful to the user relative to the label on theproduct.

In the various aspects of the present disclosure and with reference toFIGS. 3A, 3B, 3C and 3D, an exemplary version of an ingredient datamanagement platform 700 can similarly receive information from thelabels 100 of the products 110. The ingredient data management platform700 can be another embodiment of the ingredient data management platform20. The information from the labels 100 can be from a brand owner 710directly and can be in the form of the label text and graphic imagesfrom which the actual box or container art and labels are produced. Thelabels 100 can also be delivered from retailers 720. From the retailers720, the labels 100 can be the actual artwork, information, text, etc.that form the product labels. In further examples, the labels 100 caninclude images taken of the actual labels. The actual labels can be onthe product at the time or can be ready to be affixed to the product(i.e., the label flat). The retailer 720, the brand owners 710, andothers can use a mobile application 730 to send the images taken of theactual labels. Whether images, actual label art, or a feed ofinformation, the labels 100 can be received into a web upload module750.

In the various aspects of the present disclosure, the web upload module750 can communicate with a cloud storage facility 760, a database module770, and a thumbnailer module 780. The ingredient data managementplatform 700 can break down the text 104 and graphics 106 of the labels100 into the base attributes 120 that can be parsed and stored into manydifferent category modules including an ingredients module 800, a logosmodule 802, a nutrients module 804, a warnings module 806, and a claimsmodule 808. Certain aspects of the present disclosure includecategories, e.g. six categories, in which the base attributes 120 can beclassified. In certain aspects, there can a be a rest-of-product module810 that can serve as a catch-all when certain information does notpertain to the other categories. It will be appreciated in light of thedisclosure that the types or number of categories, or both, into whichthe base attributes 120 can be arranged can vary based on the type ofproduct. While the example above pertains to food, other categoriescould be implemented when needed such as for non-consumables.

In many aspects of the present disclosure, the web upload module 750 canallow drag and drop functionality to automatically upload labels 100 ofproducts 110 into the platform 20 and the computing environment. Imagescan be identified, and with drag and drop functionality, can be detectedand automatically loaded into the platform 20 and made available in thecomputing environment. In many aspects of the present disclosure, thedatabase module 770 can house metadata about the images from labels 100uploaded into the cloud storage module 760. In many aspects of thepresent disclosure, the thumbnailer module 780 can automatically takehigh-resolution images and create thumbnail images for better userexperience in analytics and API portals in the computing environment.

In many aspects of the present disclosure, the ingredients module 800can automatically identify, deconstruct, and assist with analyzing allingredients on the product 110 loaded into the computing environment toidentify its constituent information 122. In many aspects of the presentdisclosure, the logos module 802 can automatically identify and assistwith analyzing all logos and certificates (e.g., Kosher, Gluten Freecertifications, or the like) to identify such logos in the constituentinformation 122. In many aspects of the present disclosure, thenutrients module 804 can identify, deconstruct, and analyze nutrients asdetailed or outlined by the known Product Nutrient or Supplement factspanel on the label 100 or other nutrients listings in text or graphicsto automatically identify such nutrients the constituent information122. In many aspects of the present disclosure, the warnings module 806can automatically identify, deconstruct, and assist with analyzing allthe constituent information 122 in the computing environment related toallergens and other consumer warnings associated with facilities (e.g.,made in a facility that also processes peanuts), contents, combinationswith other products, or the like. Allergens identified with the warningsmodule 806 can also be automatically identified, deconstructed, analyzedand saved or associated with the metadata of the respective consumerproducts 100. In many aspects of the present disclosure, the claimsmodule 808 can receive unstructured claims data from the computingenvironment and understand the meaning of the claims in the constituentinformation 122 by using resources in the computing environment such aspattern recognition, machine learning, keyword identification, or thelike to assign appropriate base attributes 120 and master attributes124. In many aspects of the present disclosure, the rest-of-productmodule 810 can automatically identify, deconstruct, and assist withanalyzing all data on the package not captured by module 800, 802, 804,806, 808 and make that data available in the computing environment.

In many aspects of the present disclosure, the ingredient recognitionengine 900 can take the ingredients automatically captured by theingredients module 800 and can use the computing environment to parseand recognize patterns to determine and correctly identify ingredientsto assign the base attributes 120 and the master attribute 124accordingly. In many aspects of the present disclosure, the claimrecognition engine 902 can take the claims as captured by claims module808 and can automatically parse and recognize patterns to determineobjective claims (such as Hint of Salt means Low Sodium). In manyaspects of the present disclosure, the nutrient recognition engine 904can take the nutrients from the nutrients module 806 and canautomatically parse and identify true values of similar constituentingredients, such as Ascorbic Acid and Vitamin C being the same. In manyaspects of the present disclosure, the rest-of-product recognitionengine 906 can take the data from the rest-of-product module 810 and canautomatically parse, identify, and map relationships between brand andmanufacturer and flavor and product size and other data on the label nototherwise processed by the other engines 900, 902, 904.

In many aspects of the present disclosure, the attribution module 950can take base attributes 120 assigned to the constituent information 122and use recognition engines to allow for manipulation of what baseattributes 120 and master attributes 124 are associated with the variouspieces of constituent information. In many aspects of the presentdisclosure, the indexing module 960 can take the data from a relationaldatabase and index it into a NoSQL or document store for faster accessand fuzzy searching.

The information on the labels 100 can be received into the ingredientdata management platform 700 using imaging scanning and an opticalcharacter recognition (OCR) system 820 that can recognize the text 104or the graphics 106, or both, on the label 100. The graphics on thelabel can detail certifications or marketing claims such as “GlutenFree,” or “Kosher” and those too can be recognized automatically and canbe loaded into the ingredient data management platform 700. Each andevery piece of information on the labels 100 can be received into theingredient data management platform 700.

In further aspects of the present disclosure, the ingredient datamanagement platform 700 can use a combination of OCR and graphical imagerecognition (i.e., one or more recognition and comparison processes).When there is a match between the OCR and graphical image recognitionand possibly manual human data entry, the ingredient data managementplatform 700 can determine that the information is correct with thematch and accept it for the label. When there is any mismatch in theentered information, the ingredient data management platform 700 can usethis unmatched entered data as a feedback loop, and as such theingredient data management platform 700 can learn from this feedbackloop.

In some aspects of the present disclosure, the feedback loop thatindicates the error in matched information can prompt the ingredientdata management platform 700 to present the incorrectly matchedinformation from the label 100 to additional computing resources to makean automatic determination or to a data entry person (i.e., a humanchecker) when appropriate. By way of this example, when the informationrecognized by the OCR and graphical recognition systems matches enteredinformation from other computing resources; the entry of the informationis deemed correct with the match and received by the ingredient datamanagement platform 700. By way of this example, when the informationrecognized by the OCR and graphical recognition system can match theinformation entered by other computing resources, then it is deemed amatch and received into the ingredient data management platform 700.

With all of the constituent information 122 extracted from the label 100and the accuracy of its entry confirmed through the matching processesdescribed herein, the ingredient data management platform 700 can beginto associate (or confirm the association) of the base attributes 120 toeach piece of the constituent information 122 obtained from the label100. In the many aspects of the present disclosure and with reference toFIG. 3B, the ingredient data management platform 700 can include aningredient recognition engine 900, a claim recognition engine 902, anutrient recognition engine 904, and a rest-of-product recognitionengine 906. Each of the engines 900, 902, 904, 906 can deconstruct theinformation on the labels 100 that pertain to the engine and determinebase attributes 120 from that information by identifying the specificingredients, marketing statements, certifications, and claims.

Further aspects of the present disclosure include deconstructing text104 of the labels 100 that can include a compound ingredient listingfrom the ingredient listings. The ingredient recognition engine 900 ofthe ingredient data management platform 700 can recognize these compoundingredient listings and can deconstruct the compound ingredient listingsinto individual ingredients. In certain aspects, the base attributes 120can be automatically assigned to the individual ingredients recognizedin the compound ingredient listing and at least one of the baseattributes 120 can be associated with each of the individual ingredientsfrom the compound ingredient listing.

In other examples, the compound ingredient listing can include the textof a name of a mixture followed by a parenthetical in the listingcontaining the individual ingredients. By way of this example, baseattributes 120 can be automatically assigned to the individualingredients recognized in the compound ingredient listing and at leastone of the base attributes 120 can be associated with each of theindividual ingredients and categorized in the ingredients category. Inone example, the compound ingredient listing can be “7 Grain Flour Blend(Flaxseed, Barley, Oats, Spelt, Wheat, Corn, and Rice).” The ingredientrecognition engine 900 can determine that the beginning text thatannounces the mixture (i.e., “7 Grain Flour Bread) can be determined tonot be an ingredient and no base attributes would need to be assigned tothe 7-Grain Flour Bread beginning text. The individual ingredientslisted in the parenthetical (i.e., Flaxseed, Barley, Oats, Spelt, Wheat,Corn, and Rice), however, can have base attributes 120 associated withthem by the ingredient recognition engine 900. The beginning text thatannounces the mixture (i.e., 7 Grain Flour Bread) can be determined tobe relevant to the claim category, or other categories besides theingredient category, and can base attributes associated with thosecategories.

In further examples, the compound ingredient listing can include an“and/or” statement. By way of this example, base attributes 120 can beautomatically assigned to the constituent ingredients 122 recognized inthe compound ingredient listing by assuming that all of the individualingredients are present. In other examples, the retail brand user canconfirm portions of ingredients in the compound ingredient listing andbase attributes 120 can be associated accordingly with the informationfrom the brand user. In one example, the compound ingredient listing canbe “Vegetable Oil (Canola, Cottonseed, and/or Sunflower).” The beginningtext that announces the mixture (i.e., “Vegetable Oil”) can bedetermined to not be an ingredient (but an overly broad term for thesepurposes) and no base attributes need to be assigned to it as anindividual oil. Vegetable Oil is nevertheless saved to the ingredientsmodule 800 for consideration of applicability to the other baseattributes. In further examples, the beginning text that announces themixture (i.e., “Vegetable Oil”) can also be determined to be aningredient and one or more of the base attributes 120 can be assigned toit. The individual ingredients listed in the parenthetical with the“and/or” statement, i.e., “Canola, Cottonseed, and/or Sunflower,” wouldhave base attributes associated and with them in the ingredientscategory. The beginning text (i.e., “Vegetable Oil”) can be determinedto be relevant to the claim category, or other categories besides theingredient category, and can have the base attributes 120 associatedwith those categories, such as an example of a presence or a lack ofpalm oil.

The claim recognition engine 906 of the ingredient data managementplatform 700 can recognize and parse all of the claims on the labels 100including those in the text, and those in graphics. The claims can be inreference to the product contained in the container, or to the containeritself, for example how it can be recycled. The nutrient recognitionengine 904 of the ingredient data management platform 700 can recognizeand parse all of the nutrients listed on the labels 100 especiallyincluding the information in the nutritional data area of the labels100. The rest-of-product recognition engine 906 of the ingredient datamanagement platform 700 can recognize and parse all of the otherinformation on the labels 100 including those in the text, and those ingraphics. The rest-of-product recognition engine 906 can identify andparse certification statements, UPC codes, manufacturers information,and the like.

Each of the engines 900, 902, 904, 906 can deconstruct the constituentinformation 122 on the labels 100 that pertains to the products andassign base attributes 120 to that constituent information 122 byidentifying the individual ingredients, marketing statements,certifications, and claims. These engines take the plain informationfrom the label, whether it be text or graphics, or both, and assign baseattributes so that the ingredient data management platform 700 is ableto recognize every ingredient, claim, certification, or any marking,text, or graphics on the label 100. When the ingredient data managementplatform 700 is not able to recognize a word, or other text or graphicon the labels 100, the ingredient data management platform 700 can flagthe data and require further human input or further computingenvironment resources to identify it.

In the many aspects of the present disclosure, each of the engines 900,902, 904, 906 can deconstruct the constituent information 122 on thelabels 100 using pre-constructed taxonomies of many differentingredients, nutrients, claims, and other text and graphics found on thelabels 100. The taxonomies can link different individual ingredientnames by what they are the “same as” providing the ability to search andfind products that contain a specific ingredient even though thatingredient may have hundreds or thousands of unique names. Recalling theYellow 5 examples that have over 1,000 different names, the taxonomiescan group all of the “same as Yellow 5” entries together.

In the further aspects of the present disclosure, each of the engines900, 902, 904, 906 can deconstruct the constituent information 122 onthe labels 100 using rules engines to identify the many differentingredients, nutrients, claims, and other text and graphics found on thelabels 100. In other aspects of the present disclosure, each of theengines 900, 902, 904, 906 can deconstruct the constituent information122 on the labels 100 using inverted radix trees to drill down, isolateand ultimately identify all of the constituent information 122 in theform the different ingredients, nutrients, claims, and other text 104and graphics 106 found on the labels 100.

In the many aspects of the present disclosure, each of the engines 900,902, 904, 906 after deconstructing the constituent information 122 onthe labels 100 and assigning base attributes 120, can move theidentified information to the attribution module 950. The attributionmodule 950 can assign the master attributes 124 to all of theinformation identified by each of the engines 900, 902, 904, 906 but byspecifically referencing the assigned base attributes 120. Withreference to FIG. 3C, the master attributes 124 for each of the productscan be directed to an indexing module 960 and database module 970 fromthe attribution module 950. The database module 970 can be an AmazonDynamoDB brand database service. From the database module 970, theinformation can be passed to an enterprise search platform 980, such asa SOLR on Apache Lucene brand platform. The database module 970 can moveinformation to and from a cache 990, such as cloud front cache.

From the database module 970, the cache 990, and the enterprise searchplatform 980, the information with master attributes 124 assigned andsearchable (along with the base attributes 120 and constituentinformation 122 as needed) can be made available to the many differentusers through specific user interfaces 1000 and through APIs that caninteract with user interfaces or work with other systems, as shown inFIG. 3D. The user interfaces 1000 can include a user interface 1002 on amobile device, and can also include an enterprise interface 1004 thatcan be made available or can be resident on a user's computer or privatenetwork facilities. The user interface 1000 can also include a database1006 that can be queried by a user. The user interface 1000 can alsoinclude an application 1008 that can be queried by a user remotely orused in a resident or dedicated fashion. In the many aspects of thepresent disclosure, the APIs can include a smartlabel brand API 1100, aprovider API 1102, an enterprise API 1104, a mobile API 1106, and thelike. The smartlabel brand API 1100, the provider API 1102, theenterprise API 1104, and the mobile API 1106 can each be arepresentational state transfer API. That can rely on a stateless,client-server, cacheable communications protocol. In many aspects, theHTTP protocol or the HTTPS protocol can be used.

The various aspects of the present disclosure can include a customfilter that the ingredient data management platform 700 can use whendelivering the subset of master attributes 124 to the user. The user canestablish the custom filter so that the same arrangement of masterattributes 124, as determined by the user, can be repeatedly deliveredto the user in the same format established by the custom filter. Thecustom filter can serve as a custom specification where users canpre-configure one or more views. For example, the user may be mindful ofan allergy or irritant and when viewing products can highlight certainingredients that might affect the user undesirably.

Moreover, the user can amend the custom filter or specification usingthe customer user interface. Additionally, the data displayed in thecustom filter or specification can be normalized so that different userscan compare using the similarly configured filters of specifications.The user can also employ APIs to facilitate the data within third-partyapplications. Further aspects of the present disclosure can includedelivering the subset of the master attributes 124 to the user bypresenting the subset in a custom view having a first format based onone of the requests from the user and one of the products. In otheraspects, the user can be a brand owner and the presenting of the masterattributes 124 includes delivering the custom view having the firstformat determined through interaction with a brand user interface. Thebrand user interface can be configured to receive input from the branduser to deliver the custom view changed from the first format to asecond format where the second format based on the input from the branduser through the brand user interface.

In accordance with the many aspects of the present disclosure, the branduser interface 550 can use the brand user API 560 to access theingredient data management platform 20 for detailed information aboutthe ingredients provided by the brand users or manufacturers. To thisend, the brand user can connect between its own databases and those ofanother party with information from the ingredient data managementplatform 20. In other aspects, the ingredient data management platform20 can include the retailer user interface 570 and the retailer API 580that can access the ingredient data management platform 20 for detailedinformation about the ingredients that the retailer sells, including bydirect connection between the retailers own databases, inventorydatabases at various retail locations and the ingredient data managementplatform 20. The consumer user API 460 can access the ingredient datamanagement platform 20 for detailed information about the ingredients ofinterest to the consumer and can coordinate such ingredient data withuser applications, other medical programs, exercise programs, or socialmedia applications of the user. The consumer API 460 can also be used toconnect with computers in the home and those interfaces availablethrough the retailer and brand owner that can connect with theingredient data management platform 20 and the interfaces or mobiledevices of the consumer to provide the rich ingredient information tovarious systems directed by the user.

In further aspects, the retailer API 580 can be used to coordinate pointof sale transactions to provide the information from the ingredient datamanagement platform 20 to a third-party who can be tracking point ofsale transactions for that retailer. The retailer can know not only whatis being sold and how it is being sold, but the retailer can alsodetermine many different aspects of the overall sales and drill-downinto differing purchases based on the information from the ingredientdata management platform 20. Moreover, the consumer user APIs 460 can beused to coordinate to confirm purchases at the point of sale, tracknutrition, or use the data at the point of the sale and direct or portthat data into other user-preferred applications. The brand user APIs560 can also be used to track and perform analytics on the point of saletransactions to determine many different things including the success ofbrands in certain geographies, customer demand for certain ingredients,and the like. Every attribute that is associated with each of theproducts in the ingredient data management platform 20 can be associatedwith the product at the point of sale and the retailer, the brandowners, the consumer and various third-party tracking and dataaggregation entities can track these sales and perform analytics on theassociated data. This tracking can, in turn, provide for the selectionof items on retailers' shelves that more directed to the buying demandsof customers.

When a user identifies products of interest in one or more filters,profiles, or custom specifications, the ingredient data managementplatform 20 can automatically begin to build a health and nutritionprofile based on the detailed understanding of the attributes of thatproduct when associated with the consumer interest. For example, whenthe consumer shows interest in a sort of high fiber chocolate □coveredmuesli bars, the ingredient data management platform 20 can infer thatthe user is interested in high fiber and this interest can be added totheir profile. In a further example, the user can further indicateinterest in a preservative free bar or a low-calorie bar, or both, andtherefore the ingredient data management platform 20 can addpreservative free or low calorie, or both, to their profile.

In yet further aspects of the present disclosure, the user can be aconsumer and the consumer can access the ingredient data managementplatform 20 using the consumer user interface. The consumer userinterface can be used to provide a consumer label view that containsmore information that the label on the food product to which it relates.The consumer label view can be a smartlabel that is viewable through theconsumer user interface. The smartlabel can conform to the smartlabelbrand of labels. Additional aspects of the present disclosure includethe delivering the subset of the master attributes 124 includingpresenting the subset in the consumer label view to the consumer throughthe consumer user interface.

The consumer user interface can be configured to receive QR code datafrom a mobile device of the consumer and to present the consumer labelview that pertains to the QR code on the consumer user interface that ison the mobile device. In some aspects, the consumer label view cancontain information not on the label of the food product to which the QRcode data pertains.

In other aspects, the consumer user interface can be configured todisplay the consumer label view that is limited only to the food productto which the QR code pertains. In further aspects, the consumer userinterface can be configured to display the consumer label view thatdetails a grouping of food products including the food product to whichthe QR code pertains. By way of this example, the user can search for afood product with the QR code and receive a smartlabel brand label orconsumer label view through the consumer user interface.

In yet further aspects of the present disclosure, the consumer userinterface can be configured to highlight to the user the food product towhich the QR code pertains relative to other food products in a groupingof food products all of which can be related to the food productinitially identified with the QR code. By way of this example, the usercan search for a food product with the QR code and receive thesmartlabel brand label or consumer label view through the consumer userinterface that compares many related food products relative to the foodproduct identified by the QR code. In certain aspects, QR code data canbe received from the mobile device that contains at least two foodproducts. The consumer user interface can be configured to display theconsumer label view that details a grouping of food products includingthe at least two food products that pertain to the received QR codedata. In the various aspects of the present disclosure, the mobiledevice can be a smartphone, a handheld scanner, a kiosk by the consumer,and a portable computer and the consumer user interface can be on themobile device.

The smartlabel brand label can include several sections including theNutrition Facts Panel, Ingredients, Allergens, Marketing Claims, Health& Safety, GMO Disclosure, Product Instructions, Sustainability, andBrand/Company. Several of the sections listed in the smartlabel brandlabel are verbatim from the package, such as the Nutrition Facts Paneland Product Instructions sections, while others can require analysis,taxonomy based recognition and off package data generation.

In one example, the smartlabel brand label ingredient section canrequire that all ingredients be individually parsed and for theirparenthetical relationships to be displayed in a hierarchical fashion.The systems and methods disclosed herein can make this task relativelyeasy, as each ingredient can be parsed out individually whilemaintaining its order and parenthetical relationship to the otheringredients located within the ingredient declaration.

In further examples, the smartlabel brand label allergen section canhighlight the containment level of the 8 FALCPA allergens based oningredient declarations and allergen warning statements. Using thesystems and methods disclosed herein, the ingredients can be parsed andeach ingredient can be assigned FALCPA allergen properties for the threemain containment levels—Contains, May Contains and Does Not Contain.This results in an analysis that can be used to determine the FALCPAallergen containment level of each ingredient associated to anindividual product based purely on the ingredient declaration. Thesystems and methods disclosed herein further make it possible todetermine more specific containment levels such as Facility Free, SharedFacility and Shared Equipment based only on the allergen warningstatement. This result in a comprehensive allergen analysis that can beshown to allow for easy identification of the six FALCPA allergencontainment levels required as part of the smartlabel brand labelspecification.

In an additional example, the smartlabel brand label marketing claimssection can use a mixture of verbatim claims generated directly from thepackage, off package claims and derived claims from other data pointsavailable on the package. The off package and derived claims can beshown to be some of the most valuable pieces of information, as they canadd additional information and marketing ability from what is on thepackage due to limited real estate on the packaging. The systems andmethods disclosed herein can provide unique derived claims that can becreated based on using additional data points from the label. Thederived attributes can offer manufacturers' a variety of options whenimplementing the smartlabel brand label including an FDA NutrientContent Claim that utilizes nutrient analysis per serving, per ReferenceAmounts Customarily Consumed (RACC), per 100 and main/meal/individualcategory analysis, or an ingredient absence statement that relies onattributes already determined by the disclosed systems and methods. Inother aspects of the present disclosure, the ingredient data managementplatform 700 can host at least two users and each of the users being aconsumer engaged to the ingredient data management platform 700 throughthe consumer user interface. The first consumer and the second consumereach have a mobile device with the consumer user interface. In variousaspects, the consumer user interface of the first consumer creates afirst profile based on requests from the first consumer. The consumeruser interface of the second consumer creates a second profile based onrequests from the second consumer.

In further aspects of the present disclosure, the selecting of thesubset of the master attributes 124 automatically can include selectinga first subset of the master attributes 124 automatically when a firstrequest is acknowledged from the first consumer and selecting a secondsubset of master attributes 124 automatically when a request isacknowledged from the second consumer. An example of a first subset ofmaster attributes 124 can be three attributes: no Yellow 5, no sugar,and gluten free. The first subset of the master attributes 124 is basedon a combination of the request received from the first consumer, thecontextual information associated with the product, and the firstprofile. The second subset of the master attributes 124 is based on acombination of the request received from the second consumer, thecontextual information associated with the product, and the secondprofile.

Differences between the first profile and the second profile increasewith more requests from the first user or the second user, or both. Theprofiles of each of the users can develop to a point where the firstconsumer can view a certain food product using their profile in theconsumer user interface and what they see would be very different, andin some instances, drastically different then what the second consumercan view through their profile in the consumer user interface of thesame food product.

In certain aspects of the present disclosure, the ingredient datamanagement platform 20, 700 can associate all of the constituentinformation 122 obtained from the label of a food product with foodcodes recognized by the National Health and Nutrition Examination Surveybased on the base attributes determined from the label. The NationalHealth and Nutrition Examination Survey (NHANES) is a survey researchprogram conducted by the National Center for Health Statistics (NCHS) toassess the health and nutritional status of adults and children in theUnited States and to track changes over time. These NHANES food codescan be shown to aide in food-mapping to determine specific foodcompositions. In certain aspects of the present disclosure, the NHANESfood codes can also be shown to serve as a reference value to drive aunified global approach and global standard giving the ability toclassify every ingredient associated with the food product based on theNHANES food codes. In additional aspects of the present disclosure, theautomatic assigning master attributes 124 to each of the food productsis based on the base attributes 120 and includes applying food codesrecognized by the National Health and Nutrition Examination Survey tothe product based on the base attributes 120 from the ingredientscategory.

In certain aspects of the present disclosure, the ingredient datamanagement platform 20, 700 can display the information from the labels100 with reference to a reference amount customarily consumed (RACC). Inthis example, the user can be a consumer and ingredients obtained fromthe label can be displayed to the user with the RACC amounts even whenthe label lacks on RACC information. In further examples, the consumeruser interface can be configured to display the ingredients withreference to a predetermined weight per serving. In one example, thepredetermined weight per serving can be 100 grams. In further examples,the consumer user interface can be configured to display the ingredientswith reference to a recommended daily allowance.

In many aspects of the present disclosure, the brand owner can reviewand confirm the correctness of all master attributes 124, baseattributes 120, constituent information 122, and other information fromeach of its products for which labels 100 have been accepted into theingredient data management platform 700. In further aspects, the brandowners can add additional detail to or verify, or both, the informationfrom their products through the brand owner interface. The brand ownercan indicate the country of origin of the product and for eachindividual ingredient. The brand owner can further indicate at which,manufacturing facility the product is made and from where portions ofingredients have been sourced. The added information from the brandowner can be communicated to the retail user through the retail userinterface and to the consumer through the consumer interface.

In many aspects of the present disclosure, the brand owner can use thebrand user interface to display master attributes 124 associated withthe food product as selected by the brand owner to confirm and verifywhether the food product is complaint with a regulatory or certificationauthority. The master attributes 124 can be applied by the ingredientdata management platform 20 and the brand owner can be notified thatclaims on the labels 100 of the product are correct, or in someinstances, they may not be correct and can be altered. The brand userinterface can also be configured to display master attributes 124associated with the products as selected by the brand owner to confirmwhether the food product is a candidate for a certification or a claimnot already otherwise associated with the product. As such, theingredient data management platform 20 can identify for the brand ownerone or more certifications and or claims that could be applied but arenot yet on the labels 100.

In many aspects of the present disclosure, the brand owner, orretailers, or both, can use the brand user interface, retailerinterface, or a mobile application to conduct compliance checks of theirproducts before the Food and Drug Administration (FDA). The informationin the ingredient data management platform 20, 700 when related to foodcan be confirmed and verified by the FDA as a compliance check with FDAmandates for recalls, banned ingredients, FDA approvals, and the like.

In many aspects of the present disclosure, the consumer can use theconsumer user interface to explore the product base and all masterattributes 124, base attributes 120, and the constituent information 122in the ingredient data management platform 20, 700. As such, the usercan start a search based on a single ingredient. The user interface canapply various analytics that allows exploration of product categories atdifferent levels, such as based on ingredients and claims. For example,information from the ingredient data management platform 20 can revealthat one in five snacks, energy or granola bars in the US now makes anon-GMO claim of some kind. It can be shown that this food category thatincludes snacks, energy or granola bars is the leading category fornon-GMO claims, compared with an average of 4.2% for all the groceryproducts in its database.

In many aspects of the present disclosure, an image capturing computingsystem 1200 can perform the methods and processes discussed in thepresent application and depicted in FIG. 4. The image capturingcomputing system 1200 can include an image capture device 1210 that canfunctionally communicate with a processing unit 1220 of a computingdevice 1222 directly, or over a communications network 1230, which maybe an IP-based telecommunications network, the Internet, an intranet, alocal area network, a wireless local network, a content distributionnetwork, or any other type of communications network, as well ascombinations of networks.

The image capture device 1210 can be employed to automatically captureproduct information from a product or consumable good, such as an imageof a product label located on a portion of a product or consumable good,such as the label 100 (FIG. 2). In many aspects of the presentdisclosure, metadata identifying portions of the product label asgraphic or text may be encapsulated or otherwise embedded within thecaptured image. Although FIG. 4 only includes a single device, it iscontemplated that there may be multiple image capture devices 1210(e.g., remotely located, or scalable through a cloud network facility)that automatically capture product information including product labelsof products and/or consumable goods.

Each image capture device 1210 can include a scanner component 1212 thatcan function to obtain product information from a product or consumablegood. Stated differently, the scanner component 1212 can optically scansome portion of a product, such as the label 100, and output image datacorresponding to the scanned portion of the product. In one specificexample, the scanner 1212 may optically scan a barcode label or othermachine readable components of the label that can be provided onconsumer products.

The image capture device 1210 can automatically transmit the productinformation (e.g., scanned image data) and any associated metadata tothe image processing unit 1220 for processing and parsing. In someaspects, the product information may have been previously captured andstored in a database for later retrieval and processing by the computingdevice 1222, such as from the product information 1232, 1234, 1236,1238.

The processing unit 1220 may employ various optical characterrecognition (OCR) programs to process, deconstruct, and parse theproduct information and/or product image data, which generates textstrings from alphanumeric label information and generates graphicsmaps/images from graphics and/or logos included in the image data of theproduct labels. The text and/or graphics data may be compared to varioustext and graphics data in a database to return information relative tothe scanned text string(s)/graphic(s). In many aspects, the imageprocessing unit 1220 can automatically parse the product labels todetermine or otherwise identify every piece of constituent information122 on the labels 100 and assign one or more base attributes 120 to eachpiece of constituent information 122 for each product, particularlyincluding all text and graphics on the label.

In many aspects, the computing device 1222 may automatically catalog andindex or otherwise store the constituent information 122 and the baseattributes 120 in a database 1240. Although the database 1240 isdepicted as being located within the computing device 1222, it will beappreciated in light of the disclosure that the database 1240 can belocated external to the computing device 1222, such as at a remotelocation or through a cloud network facility that can be connected tothe computing device 1220 through the communications network 1230.

In many aspects of the present disclosure, an exemplary technology stack1300 can be associated with the ingredient data platform 10, as depictedin FIG. 5. The technology stack 1300 can be an embodiment of thetechnology stack in the platform 20. The technology stack 1300 canobtain constituent information 122 and provide master attributes 124 andadditional information to views, APIs, and search systems in accordancewith the present disclosure. The technology stack 1300 can connect toimage providers 1310. The image providers 1310 can provide the text 104and graphics 106 directly from the labels 100. The image providers 1310can include a collection app 1312 and digital asset managers 1314 fromwhich constituent information 122 can be exchanged or downloaded. Theimage providers 1310 can also include the labels 100 from which theconstituent information 122 can be obtained. Information from the imageproviders 1310 can be digitized at 1320. The technology stack 1300 canalso connect to data providers 1330. The data providers 1330 can providethe information relevant to each consumer products directly to theingredient data platform 10. The data providers 1330 can includeinformation obtained from product information management 1332, theglobal data synchronization network 1334, one or more nutritionaldatabases 1336, and one or more proprietary databases 1338. Informationfrom the data providers 1330 can be mapped at 1340.

From digitalization at 1320 and mapping at 1340, the information fromthe image providers 1310 and the data providers 1330 can be transformedat 1350. The transforming at 1350 can include the assignment of the baseattributes 120 and their organization under the master attributes 124.The transforming at 1350 can include accessing taxonomies at 1360 in theassignment of the base attributes 120. The transforming at 1350 providescontent for label views, APIs, and for search facilities as productdeliverables at 1400. As such, the product deliverables 1400 can supportlabel views 1410 (i.e., tailored views) including the smartlabel 1412,landing pages 1414, verification pages 1416, and the like. The productdeliverables 1400 can also support APIs 1420 including retailer APIs1422, government APIs 1424, open/free APIs 1426, and the like. Theproduct deliverables 1400 can also support information for an explorersearch so that any user can perform many different search functions onthe information from the ingredient data platform 10.

While various aspects of the present disclosure have been shown anddescribed, it will be obvious to those skilled in the art that manychanges and modifications may be made thereunto without departing fromthe spirit and scope of the present disclosure as described in thefollowing claims. All patent applications and patents, both foreign anddomestic, and all other publications referenced herein are incorporatedherein in their entireties to the full extent permitted by law.

The methods and systems described herein may be deployed in part or inwhole through a machine that executes computer software, program codes,and/or instructions on a processor. The present disclosure may beimplemented as a method on the machine, as a system or apparatus as partof or in relation to the machine, or as a computer program productembodied in a computer readable medium executing on one or more of themachines. In various aspects of the present disclosure, the processormay be part of a server, cloud server, client, network infrastructure,mobile computing platform, stationary computing platform, or othercomputing platforms. A processor may be any kind of computational orprocessing device capable of executing program instructions, codes,binary instructions, and the like. The processor may be or may include asignal processor, digital processor, embedded processor, microprocessor,or any variant such as a co-processor (math co-processor, graphicco-processor, communication co-processor and the like) and the like thatmay directly or indirectly facilitate execution of program code orprogram instructions stored thereon.

In addition, the processor may enable execution of multiple programs,threads, and codes. The threads may be executed simultaneously toenhance the performance of the processor and to facilitate simultaneousoperations of the application. By way of implementation, methods,program codes, program instructions and the like described herein may beimplemented in one or more thread. The thread may spawn other threadsthat may have assigned priorities associated with them; the processormay execute these threads based on priority or any other order based oninstructions provided in the program code. The processor, or any machineutilizing one, may include non-transitory memory that stores methods,codes, instructions, and programs as described herein and elsewhere. Theprocessor may access a non-transitory storage medium through aninterface that may store methods, codes, and instructions as describedherein and elsewhere. The storage medium associated with the processorfor storing methods, programs, codes, program instructions or other typeof instructions capable of being executed by the computing or processingdevice may include but may not be limited to one or more of a CD-ROM,DVD, memory, hard disk, flash drive, RAM, ROM, cache, and the like.

A processor may include one or more cores that may enhance speed andperformance of a multiprocessor. In certain aspects, the process may bea dual core processor, quad core processors, other chip-levelmultiprocessor and the like that combine two or more independent cores(called a die).

The methods and systems described herein may be deployed in part or inwhole through a machine that executes computer software on a server,client, firewall, gateway, hub, router, or other such computer and/ornetworking hardware. The software program may be associated with aserver that may include a file server, print server, domain server,internet server, intranet server, cloud server, and other variants suchas secondary server, host server, distributed server, and the like. Theserver may include one or more of memories, processors, computerreadable media, storage media, ports (physical and virtual),communication devices, and interfaces capable of accessing otherservers, clients, machines, and devices through a wired or a wirelessmedium, and the like. The methods, programs, or codes as describedherein and elsewhere may be executed by the server. In addition, otherdevices required for execution of methods as described in thisapplication may be considered as a part of the infrastructure associatedwith the server.

The server may provide an interface to other devices including, withoutlimitation, clients, other servers, printers, database servers, printservers, file servers, communication servers, distributed servers,social networks, and the like. Additionally, this coupling and/orconnection may facilitate remote execution of program across thenetwork. The networking of some or all of these devices may facilitateparallel processing of a program or method at one or more locationwithout deviating from the scope of the disclosure. In addition, any ofthe devices attached to the server through an interface may include atleast one storage medium capable of storing methods, programs, codeand/or instructions. A central repository may provide programinstructions to be executed on different devices. In thisimplementation, the remote repository may act as a storage medium forprogram code, instructions, and programs.

The software program may be associated with a client that may include afile client, print client, domain client, internet client, intranetclient and other variants such as secondary client, host client,distributed client, and the like. The client may include one or more ofmemories, processors, computer readable media, storage media, ports(physical and virtual), communication devices, and interfaces capable ofaccessing other clients, servers, machines, and devices through a wiredor a wireless medium, and the like. The methods, programs, or codes asdescribed herein and elsewhere may be executed by the client. Inaddition, other devices required for execution of methods as describedin this application may be considered as a part of the infrastructureassociated with the client.

The client may provide an interface to other devices including, withoutlimitation, servers, other clients, printers, database servers, printservers, file servers, communication servers, distributed servers, andthe like. Additionally, this coupling and/or connection may facilitateremote execution of program across the network. The networking of someor all of these devices may facilitate parallel processing of a programor method at one or more location without deviating from the scope ofthe disclosure. In addition, any of the devices attached to the clientthrough an interface may include at least one storage medium capable ofstoring methods, programs, applications, code and/or instructions. Acentral repository may provide program instructions to be executed ondifferent devices. In this implementation, the remote repository may actas a storage medium for program code, instructions, and programs.

The methods and systems described herein may be deployed in part or inwhole through network infrastructures. The network infrastructure mayinclude elements such as computing devices, servers, routers, hubs,firewalls, clients, personal computers, communication devices, routingdevices and other active and passive devices, modules and/or componentsas known in the art. The computing and/or non-computing device(s)associated with the network infrastructure may include, apart from othercomponents, a storage medium such as flash memory, buffer, stack, RAM,ROM, and the like. The processes, methods, program codes, instructionsdescribed herein and elsewhere may be executed by one or more of thenetwork infrastructural elements. The methods and systems describedherein may be adapted for use with any kind of private, community, orhybrid cloud computing network or cloud computing environment, includingthose which involve features of software as a service (SaaS), platformas a service (PaaS), and/or infrastructure as a service (IaaS).

The methods, program codes, and instructions described herein andelsewhere may be implemented on a cellular network having multiplecells. The cellular network may either be frequency division multipleaccess (FDMA) network or code division multiple access (CDMA) network.The cellular network may include mobile devices, cell sites, basestations, repeaters, antennas, towers, and the like. The cell networkmay be a GSM, GPRS, 3G, EVDO, mesh, or other networks types.

The methods, program codes, and instructions described herein andelsewhere may be implemented on or through mobile devices. The mobiledevices may include navigation devices, cell phones, mobile phones,mobile personal digital assistants, laptops, palmtops, netbooks, pagers,electronic books readers, music players and the like. These devices mayinclude, apart from other components, a storage medium such as a flashmemory, buffer, RAM, ROM and one or more computing devices. Thecomputing devices associated with mobile devices may be enabled toexecute program codes, methods, and instructions stored thereon.Alternatively, the mobile devices may be configured to executeinstructions in collaboration with other devices. The mobile devices maycommunicate with base stations interfaced with servers and configured toexecute program codes. The mobile devices may communicate on apeer-to-peer network, mesh network, or other communications networks.The program code may be stored on the storage medium associated with theserver and executed by a computing device embedded within the server.The base station may include a computing device and a storage medium.The storage device may store program codes and instructions executed bythe computing devices associated with the base station.

The computer software, program codes, and/or instructions may be storedand/or accessed on machine readable media that may include: computercomponents, devices, and recording media that retain digital data usedfor computing for some interval of time; semiconductor storage known asrandom access memory (RAM); mass storage typically for more permanentstorage, such as optical discs, forms of magnetic storage like harddisks, tapes, drums, cards and other types; processor registers, cachememory, volatile memory, non-volatile memory; optical storage such asCD, DVD; removable media such as flash memory (e.g. USB sticks or keys),floppy disks, magnetic tape, paper tape, punch cards, standalone RAMdisks, Zip drives, removable mass storage, off-line, and the like; othercomputer memory such as dynamic memory, static memory, read/writestorage, mutable storage, read only, random access, sequential access,location addressable, file addressable, content addressable, networkattached storage, storage area network, bar codes, magnetic ink, and thelike.

The methods and systems described herein may transform physical and/orintangible items from one state to another. The methods and systemsdescribed herein may also transform data representing physical and/orintangible items from one state to another.

The elements described and depicted herein, including in flow charts andblock diagrams throughout the figures, imply logical boundaries betweenthe elements. However, according to software or hardware engineeringpractices, the depicted elements and the functions thereof may beimplemented on machines through computer executable media having aprocessor capable of executing program instructions stored thereon as amonolithic software structure, as standalone software modules, or asmodules that employ external routines, code, services, and so forth, orany combination of these, and all such implementations may be within thescope of the present disclosure. Examples of such machines may include,but may not be limited to, personal digital assistants, laptops,personal computers, mobile phones, other handheld computing devices,medical equipment, wired or wireless communication devices, transducers,chips, calculators, satellites, tablet PCs, electronic books, gadgets,electronic devices, devices having artificial intelligence, computingdevices, networking equipment, servers, routers, and the like.Furthermore, the elements depicted in the flowchart and block diagramsor any other logical component may be implemented on a machine capableof executing program instructions. Thus, while the foregoing drawingsand descriptions set forth functional aspects of the disclosed systems,no particular arrangement of software for implementing these functionalaspects should be inferred from these descriptions unless explicitlystated or otherwise clear from the context. Similarly, it will beappreciated that the various steps identified and described above may bevaried and that the order of steps may be adapted to particularapplications of the techniques disclosed herein. All such variations andmodifications are intended to fall within the scope of this disclosure.As such, the depiction and/or description of an order for various stepsshould not be understood to require a particular order of execution forthose steps, unless required by a particular application, or explicitlystated or otherwise clear from the context.

The methods and/or processes described above, and steps associatedtherewith, may be realized in hardware, software or any combination ofhardware and software suitable for a particular application. Thehardware may include a general-purpose computer and/or dedicatedcomputing device or specific computing device or particular aspect orcomponent of a specific computing device. The processes may be realizedin one or more microprocessors, microcontrollers, embeddedmicrocontrollers, programmable digital signal processors or otherprogrammable devices, along with internal and/or external memory. Theprocesses may also, or instead, be embodied in an application specificintegrated circuit, a programmable gate array, programmable array logic,or any other device or combination of devices that may be configured toprocess electronic signals. It will further be appreciated that one ormore of the processes may be realized as a computer executable codecapable of being executed on a machine-readable medium.

The computer executable code may be created using a structuredprogramming language such as C, an object oriented programming languagesuch as C++, or any other high-level or low-level programming language(including assembly languages, hardware description languages, anddatabase programming languages and technologies) that may be stored,compiled or interpreted to run on one of the above devices, as well asheterogeneous combinations of processors, processor architectures, orcombinations of different hardware and software, or any other machinecapable of executing program instructions.

Thus, in one aspect, methods described above and combinations thereofmay be embodied in computer executable code that, when executing on oneor more computing devices, performs the steps thereof. In anotheraspect, the methods may be embodied in systems that perform the stepsthereof, and may be distributed across devices in a number of ways, orall of the functionality may be integrated into a dedicated, standalonedevice or other hardware. In another aspect, the means for performingthe steps associated with the processes described above may include anyof the hardware and/or software described above. All such permutationsand combinations are intended to fall within the scope of the presentdisclosure.

While the disclosure has been disclosed in connection with certainaspects of the present disclosure shown and described in detail, variousmodifications and improvements thereon will become readily apparent tothose skilled in the art. Accordingly, the spirit and scope of thepresent disclosure is not to be limited by the foregoing examples, butis to be understood in the broadest sense allowable by law.

The use of the terms “a” and “an” and “the” and similar referents in thecontext of describing the disclosure (especially in the context of thefollowing claims) is to be construed to cover both the singular and theplural unless otherwise indicated herein or clearly contradicted bycontext. The terms “comprising,” “having,” “including,” and “containing”are to be construed as open-ended terms (i.e., meaning “including, butnot limited to,”) unless otherwise noted. Recitation of ranges of valuesherein is merely intended to serve as a shorthand method of referringindividually to each separate value falling within the range, unlessotherwise indicated herein, and each separate value is incorporated intothe specification as if it were individually recited herein. All methodsdescribed herein can be performed in any suitable order unless otherwiseindicated herein or otherwise clearly contradicted by context. The useof any and all examples, or exemplary language (e.g., “such as”)provided herein, is intended merely to better illuminate the disclosure,and does not pose a limitation on the scope of the disclosure unlessotherwise claimed. No language in the specification should be construedas indicating any non-claimed element as essential to the practice ofthe disclosure.

While the foregoing written description enables one skilled in the artto make and use what is considered presently to be the best modethereof, those skilled in the art will understand and appreciate theexistence of variations, combinations, and equivalents of the specificaspects, method, and examples herein. The disclosure should thereforenot be limited by the above-described aspects, methods, and examples,but by all disclosure within the scope and spirit of the disclosure.

What is claimed is:
 1. A method for parsing information from a pluralityof product labels using information technology, the method comprising:obtaining, by at least one processor, constituent information from textand graphics corresponding to a product label of the plurality ofproduct labels and captured in an image by an image capture device, theconstituent information located on a portion of the product label, thetext and graphics parsed, deconstructed, and digitized; determining, bythe at least one processor, a meaning of the constituent information byanalyzing patterns in at least one of the text or graphics on theproduct label; assigning, by the at least one processor, the determinedmeaning to the constituent information as base attributes of a productcorresponding to the product label, the base attributes indicative of anintended meaning of the constituent information; associating, by the atleast one processor, the assigned base attributes with different baseattributes in at least one pre-constructed taxonomy data structure toestablish relationships between the base attributes that were previouslyassigned to the constituent information and the base attributes from thepre-constructed taxonomy data structure; assigning, by the at least oneprocessor, a primary attribute to a first relationship of theestablished relationships between the assigned base attributes and theassociated base attributes in the pre-constructed taxonomy datastructure by automatically performing one of statistical analysis andfuzzy logic; generating, by the at least one processor, a suggestion toadd to the product label a marketing claim corresponding to the product,the suggestion made in response to determining, based on the baseattributes and the primary attribute, that the product is a candidatefor the marketing claim, and wherein the marketing claim is notdisplayed in the text or graphics of the product label; and generating,by the at least one processor, at least a portion of a label viewcontaining detail based on the primary attribute pertaining to theproduct, the detail including enhanced information that is embedded intothe label view along with the text and graphics in the image captured bythe image capture device and found on the portion of the label inreal-time and that provides more information associated with the primaryattribute than is available in the text and graphics from the productlabel by displaying the enhanced information.
 2. The method of claim 1,wherein the portion of the product label for respective ones of theplurality of product labels includes items of the constituentinformation that are at least one of nutrition facts, ingredientlistings, certification listings, recycling information, warninglistings, certification statements, universal product codes,manufacturers information, marketing claims and package size.
 3. Themethod of claim 1, wherein the product for which the portion of thelabel view is generated is related to an item selected from at least oneof foods, beverages, consumer packaged goods, personal items, pet careproducts, clothing, toys, lawn care products, window stickers forvehicles, heating products, ventilation products, air conditioningproducts, or bedding products.
 4. The method of claim 1, wherein theportion of the label view is generated in response to at least one useraccessing an ingredient data platform with a device through which the atleast one user identifies at least one consumer product to obtain alabel view containing the portion of the label view with the primaryattribute descriptive of the product.
 5. The method of claim 4, whereinthe ingredient data platform is to provide information to support abrand view corresponding to the portion of the label view.
 6. The methodof claim 4, wherein the device of the at least one user is to receivecode data to present the label view that pertains to the at least oneconsumer product that is associated with the code.
 7. The method ofclaim 4, wherein the device is a mobile device, and wherein the mobiledevice is at least one of a smartphone, a handheld scanner, a kioskaccessible by the consumer, a wearable device, a laptop, a notebook, atablet, a smartwatch, or a computer.
 8. The method of claim 1, furtherincluding displaying at least the primary attribute associated with atleast one of a reference amount customarily consumed, a predeterminedweight per serving, 100 grams of weight per serving, or a recommendeddaily allowance.
 9. The method of claim 1, further including determiningthat a portion of the constituent information on the product label isincorrect.
 10. The method of claim 9, wherein upon determining that theportion of the constituent information on the product label isincorrect, the method further including generating a label portion toprovide corrected information for the product label.
 11. A systemcomprising: interface circuitry; and processing circuitry correspondingto an ingredient data platform, the processing circuitry to executeinstructions to at least: detect items of constituent information from aproduct label that corresponds to a product, the product label capturedin an image by an image capture device, the constituent informationdetected from text and graphics on the product label that have beenparsed, deconstructed, and digitized; determine a meaning of theconstituent information by analyzing patterns in at least one of thetext or graphics on the product label; assign the determined meaning asbase attributes with the ingredient data platform to the constituentinformation of the product label, the base attributes indicative of anintended meaning of the constituent information; establish relationshipsbetween the assigned base attributes with different base attributes inpre-constructed taxonomies by associating the assigned base attributesand the different base attribute in the pre-constructed taxonomies;assign a primary attribute automatically to at least one of theestablished relationships by automatically performing one of statisticalanalysis and fuzzy logic; generate a suggestion to add to the productlabel a marketing claim corresponding to the product, the suggestiongenerated in response to determining, based on the base attributes andthe primary attribute, that the product is a candidate for the marketingclaim, and wherein the marketing claim is not displayed in the text orgraphics of the product label; and configure at least one data structurefor display in a portion of a label view containing detail based on theprimary attribute that pertains to the product, wherein the detail ofthe primary attribute contains information unavailable in theconstituent information associated with the product and includesenhanced information associated with the primary attribute that providesmore information than is available in text and graphics from the productlabel of the product, the portion of the label view displaying theenhanced information that is embedded into the label view along with thetext and graphics in the image captured by the image capture device andfound on the portion of the label in real-time.
 12. The system of claim11, wherein the ingredient data platform is accessed by a user with adevice through which the user identifies the product to obtain theportion of the label view containing the primary attribute descriptiveof the product.
 13. The system of claim 12, wherein the device is toreceive code data to present the label view that pertains to the productthat is associated with the code, and wherein the device is a mobiledevice that is at least one of a smartphone, a handheld scanner, a kioskaccessible by the consumer, a wearable device, a laptop, a notebook, atablet, a smartwatch, or a computer.
 14. The system of claim 11, whereinthe ingredient data platform captures automatically, from at least oneof the text and graphics of the product label, the constituentinformation that includes at least one of nutrition facts, ingredientlistings, certification listings, recycling information, warninglistings, certification statements, universal product codes,manufacturers information, or package size.
 15. The system of claim 11,wherein the product for which the portion of the label view is generatedby the ingredient data platform is related to an item selected from atleast one of foods, beverages, consumer packaged goods, personal items,pet care products, clothing, toys for children, lawn care products,window stickers for vehicles, heating products, ventilation products,air conditioning products, or bedding products.
 16. The system of claim11, wherein the ingredient data platform is to provide information tosupport a brand view corresponding to the portion of the label view. 17.The system of claim 11, wherein the ingredient data platform displays atleast the primary attribute associated with at least one of a referenceamount customarily consumed, a predetermined weight per serving, 100grams of weight per serving, or a recommended daily allowance.
 18. Thesystem of claim 11, wherein the ingredient data platform determinesautomatically that an item of the constituent information of the productlabel is incorrect.
 19. The system of claim 18, wherein upon determiningthat the item of constituent information is incorrect, the ingredientdata platform generates a label portion to provide corrected informationfor the product label.
 20. The method of claim 1, wherein the marketingclaim is at least one of a certification listing, a certificationstatement, and a health claim.
 21. The method of claim 1, wherein themarketing claim is at least one of gluten free, non-GMO, and kosher. 22.The system of claim 11, wherein the marketing claim is at least one of acertification listing, a certification statement, and a health claim.23. The system of claim 11, wherein the marketing claim is at least oneof gluten free, non-GMO, and kosher.